Area Lead Analytics Engineer (Limited-time Relocation Bonus)

We are looking for an Area Lead Analytics Engineer to provide strategic technical leadership and shape the long-term direction of analytics engineering across the Revenue, Purchase, and Orders domains. In this role, you will act as a technical lead across multiple domains,helping build a scalable, reliable, cost-efficient, and future-proof data ecosystem.

This is a highly technical Individual Contributor role for someone who enjoys balancing hands-on engineering with strategic architectural leadership. You will define architectural standards, strengthen data modeling practices, reduce systemic complexity, and ensure that data products and pipelines are built for sustainable evolution. In addition, you will have the opportunity to drive strategic technical change and consistency that scales in the wider data science and analytics function.

You will work with a talented team of analytics engineers, Data Scientists, Engineering Managers, Product Managers, and other technical stakeholders and will sit at the intersection of hands-on technical leadership, architectural governance, strategic direction-setting, and cross-domain enablement.

In this position, you’ll

• Set the long-term technical direction for analytics engineering across the Revenue, Purchase, and Orders domains.
• Identify key intersections across Revenue, Purchase, and Orders, ensuring they are reflected consistently in data models and architecture.
• Own architectural integrity, data modeling standards, reliability, and operational quality across the area.
• Act as a central technical point of contact for cross-domain initiatives, helping teams align on technical decisions and priorities.
• Create reusable patterns, shared standards, and a common design language for analytics engineering across domains.
• Drive DSA-wide improvements in data product quality, maintainability, documentation, ownership, observability, and operational excellence.
• Reduce and govern technical debt to enable sustainable, predictable evolution of data products and pipelines.
• Translate ambiguous business and technical challenges into clear technical direction, trade-offs, and actionable next steps.
• Mentor Analytics Engineers and other ICs through technical guidance, design reviews, code reviews, and architectural feedback.
• Communicate architectural decisions, standards, and long-term implications clearly to technical and non-technical stakeholders.

• Strong experience in Data Engineering, Analytics Engineering, or related technical data roles.
• Hands-on experience designing, building, and maintaining production-grade data models, pipelines, or analytical data products at scale.
• Strong understanding of analytics engineering principles, including testing, documentation, lineage, data quality, observability, reliability, and operational excellence at scale.
• Demonstrated ability to define technical standards, reusable patterns, and architectural guardrails that improve quality and consistency across teams.
• Strong strategic and systems-thinking mindset, with the ability to spot dependencies, intersections, long-term risks, and repeated patterns across complex business areas.
• Ability to influence technical direction across multiple teams or domains without relying only on formal authority.
• Comfort working with ambiguity and translating complex problems into clear technical direction, standards, and next steps.
• Ability to balance local delivery needs with long-term architectural integrity and DSA-wide impact.
• Strong communication skills, with the ability to explain architectural trade-offs, technical decisions, and strategic priorities clearly.
• A collaborative mentoring mindset and a passion for raising the technical bar for other ICs.
• Excellent written and spoken English.

Nice to have

• Strong expertise in SQL, data modeling, and semantic layer design, with hands-on experience on dbt or similar transformation frameworks.
• Experience working with cloud data platforms (GCP, AWS, Azure, or similar)
• Experience building data products on modern data stack technologies such as BigQuery, Snowflake, Redshift, Iceberg, or similar.
• Strong practical knowledge of query performance, and cloud cost governance.
• Experience with orchestration tools such as Airflow, Dagster, or similar.
• Foundational understanding of event-driven data systems.
• Comfortable working with Feature Stores, and ML facing workloads.
• Experience with BI and reporting tools such as Power BI, Tableau, Looker, or similar.
• Experience in marketplace, e-commerce or similar business domains.
• Experience with modern data warehouses, lakehouses, and data mesh

• The opportunity to benefit from our share options programme
• 25 working days of holiday
• Access to all the tools & tech needed for work
• Home office support: we provide IT workstation equipment and a personal budget of up to 540 for home workplace furniture
• Private health insurance
• Digital mental and emotional health support and Employee Assistant Program (EAP)
• Frequent team-building events
• A personal monthly budget for shopping on Vinted
• The opportunity to spend up to 90 days per year - 21 of which can be spent working outside of the EU - on workation
• A dog-friendly office
• In Vilnius office: Gym & in-house meals at friendly prices
• In Kaunas office: a monthly lunch allowance, and a once-a-week provided in-house lunch and breakfast
• Joining us from outside Lithuania? You're eligible for our Limited-time Relocation Package! It includes a 30k gross bonus and 2 months of temporary housing (check for more info)