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Senior CockroachDB Engineers
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Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.
I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.
Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.
Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.
10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.
AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.
Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.
I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.
Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.
15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.
Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.
Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.
What our CockroachDB Developers can build

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Strengthen your existing engineering team with senior specialists who integrate seamlessly into your workflows while you retain full ownership of priorities, roadmap, and day-to-day management.
- Senior engineer(s) integrated into your team.
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Ideal for teams that need experienced engineers backed by technical leadership, ensuring faster onboarding, predictable execution, and consistent delivery without adding management overhead.
- Dedicated senior engineer(s).
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- Engineers, QA, Designers, PMs, Tech Leads - assembled to fit your project.
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Frequently Asked Questions
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How long does it typically take to hire developers with proven CockroachDB expertise?
Timelines depend heavily on sourcing method. A standard outbound search, posting a job and screening applicants from scratch, commonly takes several weeks to a few months once you account for writing a requirement profile, screening resumes, running technical interviews, and negotiating an offer. Working with a partner that maintains a pre vetted talent network built around specialists in distributed databases compresses that significantly, since the technical screening has already happened before you see a candidate. In practice, teams using a pre vetted network can move from initial conversation to a working engineer or pod in a matter of days rather than months, without sacrificing the depth of technical vetting.
What does it cost to hire a developer or team with deep CockroachDB expertise?
Cost varies with seniority, engagement model, and scope of work, but a few factors consistently drive the number. A single specialist costs less than a full pod, but a pod often delivers faster on complex work like a multi region migration because tasks run in parallel instead of queued behind one person. Engagement model matters too: a dedicated hire typically carries different overhead than a project based contract. Rather than anchoring on a headline rate, evaluate total cost against delivery speed and risk, since a cheaper hire who misconfigures replication or key design can cost far more in downtime and rework later.
What engagement models are available for CockroachDB projects, such as a dedicated hire, a pod, or a contract?
Engagement models generally fall into a few categories, and the right one depends on your scope and timeline. A dedicated hire suits an ongoing, singular need where one engineer embeds with your existing team long term. A pod, a small group assembled around your project, fits better when you need database design, migration, and application work happening in parallel under one coordinated delivery structure. A project based or contract engagement suits a defined piece of work, such as a single migration or performance audit, with a clear start and finish. Flexible partners let you start with one model and shift to another as your needs change without renegotiating from scratch.
How do you ensure time zone alignment with a team skilled in CockroachDB?
Time zone alignment starts with deliberately staffing engineers whose working hours overlap meaningfully with your own team, rather than accepting whoever happens to be available. A North America focused delivery partner sources talent with the explicit goal of matching United States and Canada business hours, which keeps daily standups, code reviews, and incident response conversations happening in real time instead of over asynchronous message threads. This matters especially for CockroachDB work, where diagnosing a live production issue, such as an unexpected hot range or a replication lag spike, benefits enormously from being able to get a knowledgeable engineer on a call immediately rather than waiting on a reply from a different working day entirely.
How does SoftDoes technically vet developers for CockroachDB expertise?
Vetting goes well beyond confirming that a candidate has listed CockroachDB on a resume. Candidates work through practical, scenario based exercises: reasoning through real EXPLAIN ANALYZE output, defending a schema and key design choice under pushback, and walking through how they would approach a multi region deployment or a hot range problem under time pressure. Evaluators probe for genuine understanding of concepts like serializable isolation, Raft based replication, and locality aware replica placement, rather than accepting surface level vocabulary. Communication and collaboration style get assessed alongside technical skill, since a technically sharp engineer who cannot work well within your existing team structure still creates friction and slows delivery.
What support is available for scaling the team after launch as our CockroachDB needs grow?
Scaling support typically includes the ability to add specialists or expand a single hire into a full pod without restarting the sourcing and vetting process from the beginning. Because the underlying talent network already exists, adding capacity means introducing a new pre vetted engineer who ramps quickly rather than opening a fresh search every time your CockroachDB workload grows. Replacement guarantees also matter here: if a team member is not the right fit as your needs evolve, a swap should happen quickly and without disrupting delivery. This flexibility lets your data infrastructure investment grow in step with actual business demand instead of being constrained by whoever you happened to hire initially.
How to Hire Developers Skilled in CockroachDB
Too many companies hire a generalist backend developer, hand them CockroachDB, and discover months later that hot ranges, misconfigured replication, or a misunderstood isolation model are quietly limiting uptime and slowing every release. The better path is hiring someone who already knows how CockroachDB behaves under real production load, how it shards data, resolves conflicts, and scales across regions without drama. This guide walks CEOs, CTOs, and VPs of Engineering through preparing an accurate requirement profile, sourcing developers with genuine CockroachDB experience, vetting them beyond a resume, and onboarding them so they ship reliable, production ready code fast.
Why CockroachDB Expertise Matters More Than You Think
What CockroachDB Engineers Actually Do Day to Day
CockroachDB is a distributed SQL database, and running it well in production looks very different from running a single instance Postgres server. Engineers with real depth in CockroachDB, sometimes described using the shorthand CockroachDB, spend their time on a specific set of recurring, technical tasks rather than generic database administration.
- Designing schemas that avoid hot ranges, using hash sharded indexes or UUID primary keys instead of sequential integers, so write heavy tables do not bottleneck on a single range when every insert lands on consecutive keys under Raft consensus across replicas.
- Configuring multi region deployments using REGIONAL BY ROW tables and locality aware replica placement, so customer data physically sits close to the users who query it most, cutting cross region latency without sacrificing consistency guarantees for regulated workloads.
- Reading EXPLAIN and EXPLAIN ANALYZE output to diagnose why a distributed query is scanning more ranges than it should, then rewriting the query or adjusting indexes so the cost based optimizer picks a cheaper physical plan across the cluster.
- Running online schema changes, adding columns or indexes on live production tables, without locking the table or scheduling a maintenance window, while confirming the change does not degrade query latency during rollout across nodes.
- Setting up incremental and locality aware backups to cloud object storage such as S3 or GCS, then testing restores regularly so recovery point objectives hold even when a node or an entire availability zone fails outright.
- Porting or extending existing PostgreSQL applications and ORMs onto CockroachDB, validating which extensions and features are and are not supported, and adjusting transaction logic for CockroachDB's default serializable isolation instead of relying on row level locking.
The Business Case for Real CockroachDB Depth
Hiring for surface level familiarity instead of proven depth shows up later as outages, rewrites, and missed deadlines. Here is what genuine CockroachDB expertise buys your organization in concrete, operational terms.
- System stability: because CockroachDB replicates data with Raft consensus and survives node or zone failures automatically, teams with engineers who understand that architecture avoid the two a.m. outages that come from someone treating a distributed database like a single server instance.
- Faster delivery cycles: engineers fluent in CockroachDB use online schema changes and the built in optimizer tooling to ship features and migrations without waiting for maintenance windows, keeping your release cadence tied to product priorities instead of database constraints.
- Lower technical debt: developers who understand hot range mitigation and proper key design from day one avoid the costly schema rewrites that undersized teams face later, when a sequential primary key finally chokes write throughput under real production load.
- Scalable architecture: specialists who configure multi region and locality aware deployments correctly the first time give you a data layer that expands with new markets and user growth, instead of a rebuild project disguised as a scaling initiative.
Getting Your Hiring Plan Right Before You Post a Single Job
Defining What You Actually Need Before You Start Sourcing
Before writing a single job post, get internal agreement on what problem you are actually solving. A team asking for "a CockroachDB developer" without first mapping scope, seniority, and delivery model ends up interviewing candidates against a moving target and losing strong applicants to slower decision cycles.
Map Your Project Scope and Architecture Requirements First
Start by defining exactly what the CockroachDB work touches: a new greenfield service, a migration from an existing PostgreSQL system, or a multi region expansion of a cluster already in production. Each scenario calls for a different mix of schema design, data migration, and operational skill. If your team lacks the internal expertise to define this scope precisely, working with a partner that offers database design and development consulting before you hire can save months of rework and prevent you from writing a requirement profile around the wrong problem entirely.
Match Seniority to the Complexity of Your Stack
A junior developer can maintain an existing CockroachDB schema, but designing one from scratch, planning a multi region rollout, or diagnosing a distributed query regression calls for someone who has done it before under real load. Match seniority to complexity honestly. Complementary stack matters too: strong SQL fundamentals, familiarity with Kubernetes or your chosen orchestration layer, and comfort with observability tooling all shape how fast a new engineer becomes productive on your specific system.
Deciding Between an In House Hire and a Dedicated Remote Pod
A single in house hire works when you have one clear, ongoing need and existing engineering leadership to manage them. A dedicated remote pod, a small team assembled around your project rather than a lone freelancer, fits better when you need database design, migration, and application level work done in parallel, or when your timeline does not allow for a slow single hire search. Neither option is inherently better, only better suited to your scope and internal capacity.
Writing a Requirement Profile That Attracts Real CockroachDB Experts
A vague job description filters out the strong candidates first, because experienced engineers skip postings that read like generic database administrator listings. A profile that attracts real CockroachDB talent covers four things clearly.
- The technical mission: state plainly what the engineer will actually build or fix, such as designing a multi region schema, resolving hot range issues, or migrating an existing Postgres workload, so serious candidates can self select based on real fit.
- The ecosystem and tooling: name the specific stack, orchestration layer, observability tools, and deployment targets, so candidates understand exactly what they will be working inside rather than guessing at your environment from a generic listing.
- Team dynamics: describe who the engineer reports to, whether they join an existing pod or lead a new initiative, and how decisions on schema and architecture get made, since senior candidates weigh autonomy heavily when evaluating an offer.
- System impact: explain what depends on this work succeeding, whether it is uptime for a customer facing product, latency for a global user base, or compliance with data residency rules, so the role reads as consequential rather than routine.

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Finding, Vetting, and Onboarding the Right Team
How to Actually Vet CockroachDB Skill, Not Just Resumes
Resumes list technologies; they rarely prove anyone can operate a distributed database under real constraints. A candidate can genuinely believe they know CockroachDB after running a single node locally for a side project, without ever having faced a live replication lag spike or a cluster wide rebalance under production traffic. Getting this right means being deliberate about where you look for candidates and how you test them once they apply, rather than trusting a keyword match on a resume to stand in for real operational experience.
Where to Find Developers Who Have Really Run CockroachDB in Production
Standard outbound recruiting casts a wide net but often surfaces developers who have only touched CockroachDB briefly on one project. Pre vetted talent networks with a proven CockroachDB track record shortcut that problem, since candidates have already been screened for depth before you ever see a profile. Browsing an established talent network built around this kind of specialist skill gets you to a shortlist of proven engineers faster than posting a job and waiting for applications to arrive.
Testing for Judgment, Not Just Vocabulary
The strongest signal is a practical exercise: a live coding session or a system design conversation centered on an actual CockroachDB scenario, such as diagnosing a hot range or planning a multi region rollout. Ask candidates to reason through EXPLAIN ANALYZE output or defend a key design choice under pushback, and watch how they respond when you push back on their first answer, since a candidate who can only recite one correct approach without weighing alternatives usually has not operated the database under enough different conditions to be trusted with your production cluster. Pair that with a conversation about how they handle ambiguity and disagreement, since culture fit determines whether strong technical judgment actually reaches production. A candidate who can explain a tradeoff clearly but also knows when to escalate rather than push a risky schema change alone is worth more than one who is simply fast.
Onboarding and Integration: A 30/60/90 Day Setup
- Days one through thirty: grant repository and cluster access, walk the new hire or pod through your schema, replication topology, and existing hot spots, and pair them with an internal engineer on a small, well scoped fix so they build real familiarity with your system before touching anything critical.
- Days thirty one through sixty: hand off a meaningful piece of ownership, such as a schema migration or a performance investigation, while keeping regular check ins to catch misunderstandings about your architecture early, before they turn into a production incident affecting real customers.
- Days sixty one through ninety: expect independent delivery on production ready code, including schema changes and query optimization work done without close supervision, and use this window to decide whether the engagement should scale into a larger pod or a longer term arrangement.
Making the Right Call
Red Flags and Green Flags to Watch For
Red flags: a candidate who cannot explain why sequential primary keys create write bottlenecks in CockroachDB; someone who defaults to manual row locking logic instead of trusting serializable isolation; vague or evasive answers when asked to read real EXPLAIN ANALYZE output; no direct experience configuring multi region or locality aware deployments despite claiming senior status; and a tendency to describe every past project in glowing, conflict free terms, since real distributed database work always involves at least one hard incident worth discussing honestly.
Green flags: fluent, specific talk about hash sharded indexes and UUID keys as hot range mitigations; clear reasoning about tradeoffs between consistency and latency in multi region setups; hands on comfort walking through a query plan and explaining exactly why it is scanning too many ranges; direct experience running online schema changes against a live production system; and a willingness to describe a mistake they made in production and what they changed afterward, since that kind of honesty tends to correlate with real operational depth rather than rehearsed talking points.
Why Partnering with SoftDoes Gives You an Edge
SoftDoes is a North America focused software engineering and talent delivery partner serving clients across the United States and Canada, giving you immediate access to pre vetted senior developers with real CockroachDB experience rather than a slow, uncertain independent search. You get a team delivery model, not an isolated freelancer disappearing mid project, backed by replacement and scaling guarantees if a fit is not right. Engagement models flex from a single specialist to a full pod, and because CockroachDB shares the PostgreSQL wire protocol, many clients pair a CockroachDB specialist with our PostgreSQL developers for hybrid environments without adding separate vendor relationships or coordination overhead.
Ready to Hire CockroachDB Engineers?
If your team needs a developer or a full pod with genuine, production tested CockroachDB experience, waiting on a slow, uncertain hiring cycle costs you momentum you cannot get back. SoftDoes gives you access to pre vetted senior talent, flexible engagement models, and delivery guarantees built for teams that need to move now. Schedule a consultation or discovery call with SoftDoes today, and start building your CockroachDB team with confidence instead of guesswork.

















































