Momentum Worldwide
Lead Data Engineer, Technology Consulting
- Compensation
- £60K–£100K / yr
- Location
- London, United Kingdom
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Full time
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Demonstrated ability to lead multiple complex areas of data engineering delivery to time, cost and quality with minimal direction.
- Experience managing teams inclusively, delivering agreed scope and acting as an escalation point for decisions affecting your work.
- Experience building data pipelines using Spark, Python or SQL.
- Experience with AWS and its data and AI/ML services, such as SageMaker.
- Experience with big data and lakehouse platforms on AWS, such as EMR, Databricks or Snowflake.
- Experience building data platforms, including Data Lakes, Lakehouses or Data Meshes, to support analytics and AI workloads.
- Understanding of data security, data governance and responsible AI principles.
- Ability to partner with and influence senior stakeholders and build trust across stakeholder groups.
- Track record of anticipating project risks and bringing multidisciplinary subject matter experts together to analyse and resolve issues.
- Recognised subject matter expertise, with the ability to drive innovation and bring experience from multiple clients and industries.
- Commitment to self‑improvement and learning, including learning new programming languages.
- Pragmatic problem‑solving skills and the ability to create clarity and structure in ambiguous situations.
- Experience productionising and operating data and AI/ML solutions, including Generative AI or LLM‑based applications.
- Experience coaching and mentoring engineers and creating structured development opportunities for junior team members and client counterparts.
Full description
Salary: £60,000 - 100,000 per year
Requirements:
- Demonstrated ability to lead multiple complex areas of data engineering delivery to time, cost and quality with minimal direction.
- Experience managing teams inclusively, delivering agreed scope and acting as an escalation point for decisions affecting your work.
- Experience building data pipelines using Spark, Python or SQL.
- Experience with AWS and its data and AI/ML services, such as SageMaker.
- Experience with big data and lakehouse platforms on AWS, such as EMR, Databricks or Snowflake.
- Experience building data platforms, including Data Lakes, Lakehouses or Data Meshes, to support analytics and AI workloads.
- Understanding of data security, data governance and responsible AI principles.
- Ability to partner with and influence senior stakeholders and build trust across stakeholder groups.
- Track record of anticipating project risks and bringing multidisciplinary subject matter experts together to analyse and resolve issues.
- Recognised subject matter expertise, with the ability to drive innovation and bring experience from multiple clients and industries.
- Commitment to self‑improvement and learning, including learning new programming languages.
- Pragmatic problem‑solving skills and the ability to create clarity and structure in ambiguous situations.
- Experience productionising and operating data and AI/ML solutions, including Generative AI or LLM‑based applications.
- Experience coaching and mentoring engineers and creating structured development opportunities for junior team members and client counterparts.
- Active SC clearance is required.
- Desirable: Experience building automated data quality checks and metrics.
- Desirable: Experience creating or maintaining production software delivery pipelines using CI/CD tools such as GitHub Actions, Azure DevOps, Jenkins or CircleCI.
- Desirable: Experience building LLM or foundation‑model applications using frameworks such as LangChain, vector databases or agentic AI approaches.
- Desirable: Experience with MLOps and Infrastructure as Code, such as Terraform or CloudFormation, for data, analytics and AI services.
- Desirable: Experience with data reporting and visualisation tools such as Power BI, Tableau or Qlik.
- Desirable: Experience applying AI or agentic techniques in your work using GitHub Copilot, Claude Code or equivalent.
Responsibilities:
- Lead delivery of complex data engineering work across multiple areas, ensuring delivery to agreed time, cost and quality.
- Build modern, AI-enabled data platforms on AWS, including distributed workloads, batch and streaming pipelines, and data foundations for machine learning, Generative AI and LLM solutions.