Lead AI Data Engineer
Posted Today by Airswift
Negotiable
Inside
Remote
Europe, Poland
Summary: The Lead AI Data Engineer will be responsible for defining and scaling modern data practices for an innovative energy intelligence platform. This role involves leading advanced data modeling initiatives, implementing data governance frameworks, and promoting a data-driven culture across teams. The position is a long-term freelance contract with full-time hours, primarily remote from Europe. The ideal candidate will possess expert-level skills in SQL and dbt, along with strong stakeholder management abilities.
Key Responsibilities:
- Define and enforce best practices across the data ecosystem (CI/CD, modular architecture, testing)
- Lead advanced data modelling initiatives using SQL and dbt, ensuring scalable and reusable design
- Design and implement robust data governance frameworks, including GDPR response ownership
- Partner with Product to shape the Analytics Engineering roadmap and translate business needs into technical solutions
- Promote a data-driven culture and influence standards across multiple teams
Key Skills:
- Expert-level SQL and dbt experience (clean, testable, modular code)
- Strong expertise in dimensional data modelling and complex data scenarios
- Proven experience driving adoption of engineering standards across teams
- Excellent stakeholder management and communication skills (technical ? non-technical translation)
- Deep understanding of the end-to-end data lifecycle (ingestion ? transformation ? consumption)
Salary (Rate): undetermined
City: undetermined
Country: Poland
Working Arrangements: remote
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Job Title: Lead AI Data Engineer (Energy Intelligence Platform)
Duration: Contract (long-term engagement)
Workload: Full time hours
Setup: Freelance (Daily rate / Limited Company / Umbrella / Sole Trader)
Location: Remote from Europe
We are looking for a Lead Data Engineer to define and scale modern data practices for a cutting-edge energy platform driving real-time decision-making.
Key Responsibilities:
- Define and enforce best practices across the data ecosystem (CI/CD, modular architecture, testing)
- Lead advanced data modelling initiatives using SQL and dbt, ensuring scalable and reusable design
- Design and implement robust data governance frameworks, including GDPR response ownership
- Partner with Product to shape the Analytics Engineering roadmap and translate business needs into technical solutions
- Promote a data-driven culture and influence standards across multiple teams
Must-Have Skills:
- Expert-level SQL and dbt experience (clean, testable, modular code)
- Strong expertise in dimensional data modelling and complex data scenarios
- Proven experience driving adoption of engineering standards across teams
- Excellent stakeholder management and communication skills (technical ? non-technical translation)
- Deep understanding of the end-to-end data lifecycle (ingestion ? transformation ? consumption)
Nice-to-Have:
- Experience owning long-term data modelling strategy
- Hands-on implementation of data governance frameworks
- Exposure to handling GDPR/data privacy incidents
- Experience leading proof-of-concepts (PoCs) for new technologies
- Contribution to broader data strategy and organisational data culture