Senior Analytics Engineer
The team waiting for you:
As our Senior Analytics Engineer, you will bridge the gap between complex engineering infrastructure and commercial decision-making, taking full ownership of our core metrics and data modeling. We are rapidly scaling our data ecosystem to handle hundreds of terabytes, making this the perfect time to build scalable data models, streamline automated workflows, and shape our overall analytics architecture. Your challenge is to tame massive, high-volume datasets into trusted, actionable insights while building robust end-to-end data automations that directly impact business growth.
In this role, you will:
Partner with analysts to define and maintain the global view of company metrics, participating in discussions to support crucial commercial decisions;
Push the limits of dbt by developing scalable data models and writing custom macros to handle complex business logic, ensuring our code remains DRY and efficient;
Build end-to-end automations (using Python and Airflow) to handle API integrations and reverse ETL processes that sync data back to operational systems;
Manage data pipelines by implementing rigorous monitoring and data quality tests to guarantee trust in the numbers.
Your skills & experiences:
dbt Mastery: Advanced experience structuring dbt projects, optimizing performance, and building custom macros for complex business logic.
Core Technical Stack: Advanced proficiency in SQL alongside strong programming skills in Python for building robust pipeline automations.
Modern Data & DataOps Practices: Strong experience with cloud data platforms (GCP, AWS, or Snowflake) paired with hands-on practice in Git, Docker, and CI/CD pipelines.
Prototyping & Ownership: High sense of ownership with the ability to prototype automated solutions quickly and actively contribute to deep engineering discussions.
Languages: Professional written and spoken fluency in both English and Lithuanian.
Nice to have:
Experience implementing reverse ETL patterns or operational analytics pipelines.
Background working in e-commerce, web scraping, or other high-volume, high-throughput data domains.
Tech stack:
Data Warehousing & Ingestion: Google Cloud Platform (BigQuery, Pub/Sub, GCS)
Data Modeling & Orchestration: dbt, SQL, Apache Airflow, Python
Visualization & Analytics: Power BI, Apache Superset
Deployment & Tooling: Kubernetes, Docker, Git, Cursor / Claude Code
Salary & Benefits:
Gross salary: 3500 - 6000 EUR/month. Keep in mind that we are open to discuss a different salary based on your skills and competencies.
Growth & Learning: 40+ internal learning options, external conferences, mentorship, and year-round knowledge-sharing.
Health & Well-being: Private health insurance, psychotherapy, on-site well-being consultants, 24/7 gym access, and a wellness app.
Celebration & Community: Team events, an overseas workation, quarterly team-building budgets, and plenty of ways to mark milestones together.
Plus bonus vacation days, paid life-moment days off, barista coffee, and all the tools you need. See the full list of benefits here: https://career.oxylabs.io/blog/our-work-benefits/.