At a glanceSummarised by Seekless from the posting.
Must have8
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 have5
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
Skills
Python
SQL
Airflow
Azure
Snowflake
Docker
CI/CD
Terraform
Claude
Cursor
Java
JavaScript
React
Prefect
Dagster
Full-time B2B | Remote EU / Poland | US Sports Insurance Context
About the company
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
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Build and maintain reporting outputs for insurance carriers and partners (bordereau reporting)
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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!
Legal
The controller of the data contained in your application is Sunscrapers Sp. z o.o., operating under the Vecten brand, ul. Tadeusza Czackiego 15/17, 00-043 Warsaw, Poland, NIP 1182116268. We process your data in order to assess your application for the role you are applying for. You have the right to access, rectify, erase and restrict the processing of your data, and the right to lodge a complaint with the President of the Polish Data Protection Authority. For data protection matters write to [email protected]. Full information, including the legal bases, recipients and retention periods, is set out in our Privacy Policy