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Full-time B2B | Remote EU / Poland | US Sports Insurance Context We are an AI-native data and technology partner for private capital and healthcare. Founded in 2010 and headquartered in Warsaw, we work with leading PE firms, VC funds, and healthcare organizations to build proprietary data infrastructure, deploy AI solutions, and drive AI-native transformation. Our clients manage a cumulative $1.2T+ in assets. Our average engagement runs five years. Our NPS sits above 80. We don't need to claim credibility - we can show it. We've also done to ourselves what we now do for clients. We've restructured our own company around AI - tools, policies, roles, delivery models. This isn't a pitch. It's a playbook we've already run, and we're hiring the engineers who will run it for others. The Opportunity Our client is a US insurance leader for youth and college sports - they insure athletes, teams, and organizations, including innovative products that price injury and transfer risk for college athletes in the NIL era. Their data estate is at an inflection point: a legacy enterprise ETL platform is being decommissioned this fall, pipelines are moving to a modern orchestration stack, and the whole platform is consolidating onto Azure. You'll join a small senior pod (a tech lead and a senior backend engineer) as the full-time engineering backbone of the account. This is not a ticket-taking role. The client environment is fast-moving and sometimes ambiguous - we're expected to propose, decide, and deliver, not wait for specs. You'll work directly with the client's CTO-level stakeholders and with their partner vendors' engineering teams. What you'll be doing The core of the work is rebuilding and running the client's data platform: replacing legacy ETL with new pipelines, operating a medallion (bronze/silver/gold) architecture across Azure and Snowflake, productionizing ML scoring pipelines that currently live in data scientists' Jupyter notebooks, and owning the infrastructure underneath it all - including an ongoing AWS-to-Azure migration and cloud cost cleanup. Around that core, expect a long tail of adjacent work: reporting pipelines for insurance carriers, third-party sports data feeds, the occasional Java service or frontend fix. We’re looking for someone with core expertise in data engineering but who’s not afraid to touch devops, backend or even some sporadic frontend work. Your Responsibilities: Design, build, and operate data pipelines in Airflow (or similar) across Azure and Snowflake, replacing a legacy ETL platform Productionize ML and scoring workflows (injury-risk and pricing models) from Jupyter notebooks into reliable, scheduled pipelines with seasonal retraining runs Ingest and manage third-party data feeds (sports data providers such as Sportradar) and internal application databases Build and maintain reporting outputs for insurance carriers and partners (bordereau reporting) Own DevOps for the data platform: Azure infrastructure, IaC, CI/CD, monitoring, secrets, and access management Support the AWS-to-Azure migration and infrastructure cost optimization Collaborate directly with client stakeholders and external vendor teams across multiple parallel workstreams, largely async (Jira, Slack) Requirements Required Skills & Experience: Senior-level data engineering: strong Python and SQL, solid data modeling, and production experience with a modern orchestrator (Prefect, Airflow, or Dagster) Solid hands-on Azure experience - data services, storage, compute, networking, and identity - and confidence running production workloads on it Experience with Snowflake (or another cloud data warehouse) in production DevOps skills applied to data platforms: Docker, CI/CD, infrastructure-as-code (Terraform or similar), monitoring and alerting AI-native way of working: you use tools like Claude and Cursor as a core part of how you deliver, including outside your comfort zone Flexibility and ownership: willing to pick up work beyond pure data engineering (a Java service, a frontend tweak, an infra incident) and see it through Self-directed: able to scope ambiguous requests, propose solutions, and deliver without heavy oversight Fluent English and clear, proactive communication with non-technical stakeholders Nice to Have: Cloud migration experience - moving workloads, databases, and pipelines between clouds or platforms Experience in insurance, financial services, or other regulated environments MLOps exposure - model training infrastructure, feature pipelines, scheduled scoring Reading-level comfort with Java and JavaScript/React codebases Experience taking over and stabilizing systems built by someone else Benefits Unrestricted AI Stack & Premium Gear: Fully paid licenses for Cursor, Claude Pro, etc. Total Autonomy (Remote-First): No filler meetings, no Jira bloat, no micromanagement. You own the workflow. We care about shipped systems in production, not logged hours. Direct Impact: You'll work face-to-face with our CEO, CTO & VPs and directly with client leadership. Frontier Engineering Culture: Build alongside elite engineers who are shipping systems that drive real business decisions. Backed by continuous growth and a strong knowledge-sharing culture (check our YouTube). Sounds like a perfect place for you? Don't hesitate to click apply and submit your application today!
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.