> Markdown version of [/jobs/ext/4696544-data-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/4696544-data-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data & Analytics Engineer - **Company:** Polarsteps - **Location:** Amsterdam, Netherlands (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Airflow, Amazon Web Services, App Store (IOS), Microsoft Azure, BigQuery, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Mobile Application Software, Marketing Information Systems, Mixpanel, Twilio, Data Ingestion, Large Language Models, Snowflake, Core Api, Vertica, Claude, Terraform, Looker Analytics, Amazon Redshift - **Published:** November 13, 2026 - **Apply:** https://jobs.ashbyhq.com/polarsteps/264bba44-d088-419f-9674-d1f54a04caa1/application ## About the Role 5+ years of experience in data engineering, analytics engineering or a hybrid data role, ideally in a B2C product or mobile app company. Strong SQL and Python, and hands-on experience modeling large event datasets in a modern warehouse (e.g. ClickHouse, Snowflake, BigQuery, Redshift). Experience with dbt and an orchestration tool such as Airflow or Dagster. Proven track record of bringing structure to data governance: tracking plans, event ownership, documentation and data quality. Experience with product analytics tools (e.g. Mixpanel, Amplitude) and BI tools (e.g. Metabase, Looker). Comfortable owning infrastructure decisions: cloud (AWS/GCP/Azure), infrastructure-as-code (e.g. Terraform), CI/CD for data. A pragmatic, ownership-driven mindset: you're happy to set the strategy and get your hands dirty, and you enjoy the hygiene work others tend to avoid. Excellent communication skills: you can explain trade-offs to engineers and to non-technical stakeholders alike. Bonus points if you have: Experience with mobile attribution or marketing data (e.g. AppsFlyer, SKAdNetwork, ad platform APIs). Experience with reverse ETL or CDPs (e.g. RudderStack, Twilio Segment). Experience with experimentation data and A/B testing infrastructure. Knowledge of GDPR and handling personal data responsibly in an analytics stack. ## Description As our first Senior Data & Analytics Engineer, you'll own the foundation that every data-driven decision at Polarsteps is built on. Product & growth teams run experiments and analyse the data every week, leadership need clear reports for investors, and all of that depends on data that is reliable, modelled and compliant. You'll set the direction for our data platform, bring structure to data governance, and own the data infra that helps our product managers, marketers and data scientists do their job even better. You'll work closely with the Head of Engineering on infrastructure and architecture, and with the Head of Growth and product teams on what the business needs from data. With 20M+ users and ratings of 4.8 and 4.7 on the app stores and features in multiple Google and Apple showcases, we've got an impressive past. But we're even more excited for the future, and you'll play a crucial role in building the data foundation that gets Polarsteps to 100M+ travelers around the globe., * Own the data platform roadmap: set the strategy for our data infrastructure and warehouse, make the build-vs-buy and tooling calls, and oversee execution together with DevOps. * Design, build and maintain scalable ingestion pipelines for both internal (product events, back-end data) and external sources (ad platforms, attribution, app store data). * Build and maintain a clean, documented modeling layer (e.g. dbt) that serves as the single source of truth for analysts, data scientists and self-serving PMs. * Lead data governance: define and enforce event naming and tracking standards, a schema change process, documentation, and dashboard ownership. * Embed privacy in the data stack: make sure personal data is categorized, minimized and pseudonymized before it reaches downstream and third-party tools, in close collaboration with Legal * Own the health of the stack: monitoring, alerting, data quality checks and cost management, so issues are caught before they reach stakeholders. * Define who owns what across our data tooling (e.g. Mixpanel, our warehouse and BI layer), and help teams get the most out of self-serve analytics. * Enable data enrichment to unlock deeper insights for Product and Growth. * Explore how we can safely use LLMs (such as Claude) on top of our data for analysis and reporting. * Act as the go-to data partner for Product, Engineering and Growth, and help grow the data function as Polarsteps scales.