Job Summary
The Senior Technical Lead will be responsible for leading technical teams and overseeing the implementation of projects related to Snowflake, Azure Data Factory (ADF), and Data Bricks. The role involves ensuring the successful delivery of data solutions and optimizing data pipelines for efficient performance.
Data Engineer
Our Data Engineers play a key role in evolving our data platform – responsible for the design, build and support of secure, scalable and trusted data pipelines that power critical products and insights across the organisation. Our data platform supports a wide range of audience, content and commercial use cases. It processes large‑scale event and relational data to power analytics, reporting, experimentation, and downstream products across BBC Studios, with a strong emphasis on data trust, security and governance.
Key Responsibilities
- Build and maintain high‑quality, automated data pipelines for ingesting, transforming and publishing data.
- Ensure data pipelines follow agreed standards for reliability, scalability, security and performance.
- Work with senior engineers and architects to implement core platform patterns, tooling and capabilities.
- Apply appropriate security, privacy and governance controls to protect audience data and enable its safe, compliant use.
- Collaborate closely with engineers, product, analytics and data governance partners to deliver valuable data solutions.
- Support the platform in production, contributing to monitoring, incident resolution and continuous improvement.
- Continuously learn and stay up to date with data engineering tools, technologies and ways of working.
Required Skills & Experience
- Experience building or supporting data pipelines for analytics or data platforms.
- Strong SQL skills and experience working with data warehouses and transformation tools (e.g. dbt).
- Understanding of data modelling and good database design practices.
- Familiarity with pipeline orchestration and automated data workflows.
- Good engineering practices: writing clean, maintainable code, testing, and working with CI/CD pipelines
- Comfortable working in an agile delivery environment (Scrum or Kanban).
- Familiarity with cloud platforms and infrastructure-as-code concepts (preferably AWS and Terraform).
- A collaborative mindset and ability to work effectively within a team
Desirable Skills & Experience
- Experience with Python or another high‑level programming language
- Familiarity with large‑scale data processing technologies
- Exposure to Snowflake or similar cloud data warehouses
- Experience using AI‑assisted development tools (e.g. Copilot, Claude) to improve productivity
Key Responsibilities
Data Engineer
Our Data Engineers play a key role in evolving our data platform – responsible for the design, build and support of secure, scalable and trusted data pipelines that power critical products and insights across the organisation. Our data platform supports a wide range of audience, content and commercial use cases. It processes large‑scale event and relational data to power analytics, reporting, experimentation, and downstream products across BBC Studios, with a strong emphasis on data trust, security and governance.
Key Responsibilities
- Build and maintain high‑quality, automated data pipelines for ingesting, transforming and publishing data.
- Ensure data pipelines follow agreed standards for reliability, scalability, security and performance.
- Work with senior engineers and architects to implement core platform patterns, tooling and capabilities.
- Apply appropriate security, privacy and governance controls to protect audience data and enable its safe, compliant use.
- Collaborate closely with engineers, product, analytics and data governance partners to deliver valuable data solutions.
- Support the platform in production, contributing to monitoring, incident resolution and continuous improvement.
- Continuously learn and stay up to date with data engineering tools, technologies and ways of working.
Required Skills & Experience
- Experience building or supporting data pipelines for analytics or data platforms.
- Strong SQL skills and experience working with data warehouses and transformation tools (e.g. dbt).
- Understanding of data modelling and good database design practices.
- Familiarity with pipeline orchestration and automated data workflows.
- Good engineering practices: writing clean, maintainable code, testing, and working with CI/CD pipelines
- Comfortable working in an agile delivery environment (Scrum or Kanban).
- Familiarity with cloud platforms and infrastructure-as-code concepts (preferably AWS and Terraform).
- A collaborative mindset and ability to work effectively within a team
Desirable Skills & Experience
- Experience with Python or another high‑level programming language
- Familiarity with large‑scale data processing technologies
- Exposure to Snowflake or similar cloud data warehouses
- Experience using AI‑assisted development tools (e.g. Copilot, Claude) to improve productivity
Skill Requirements
2. Strong experience in azure data factory (adf) for data integration and orchestration.
3. Handson knowledge of data bricks for data engineering, data processing, and machine learning.
4. Ability to design, develop, and optimize complex data pipelines for etl processes.
5. Strong problem-solving skills and the ability to troubleshoot data pipeline issues.
6. Excellent communication skills to interact with technical and nontechnical stakeholders effectively.
7. Strong leadership skills to guide and motivate technical teams towards project delivery and success.
8. Experience in agile methodologies and project management practices for efficient project execution.
Other Requirements
1.Relevant certifications in Snowflake, Azure Data Factory (ADF), DataBricks are a plus.
Data Engineer
Our Data Engineers play a key role in evolving our data platform – responsible for the design, build and support of secure, scalable and trusted data pipelines that power critical products and insights across the organisation. Our data platform supports a wide range of audience, content and commercial use cases. It processes large‑scale event and relational data to power analytics, reporting, experimentation, and downstream products across BBC Studios, with a strong emphasis on data trust, security and governance.
Key Responsibilities
- Build and maintain high‑quality, automated data pipelines for ingesting, transforming and publishing data.
- Ensure data pipelines follow agreed standards for reliability, scalability, security and performance.
- Work with senior engineers and architects to implement core platform patterns, tooling and capabilities.
- Apply appropriate security, privacy and governance controls to protect audience data and enable its safe, compliant use.
- Collaborate closely with engineers, product, analytics and data governance partners to deliver valuable data solutions.
- Support the platform in production, contributing to monitoring, incident resolution and continuous improvement.
- Continuously learn and stay up to date with data engineering tools, technologies and ways of working.
Required Skills & Experience
- Experience building or supporting data pipelines for analytics or data platforms.
- Strong SQL skills and experience working with data warehouses and transformation tools (e.g. dbt).
- Understanding of data modelling and good database design practices.
- Familiarity with pipeline orchestration and automated data workflows.
- Good engineering practices: writing clean, maintainable code, testing, and working with CI/CD pipelines
- Comfortable working in an agile delivery environment (Scrum or Kanban).
- Familiarity with cloud platforms and infrastructure-as-code concepts (preferably AWS and Terraform).
- A collaborative mindset and ability to work effectively within a team
Desirable Skills & Experience
- Experience with Python or another high‑level programming language
- Familiarity with large‑scale data processing technologies
- Exposure to Snowflake or similar cloud data warehouses
- Experience using AI‑assisted development tools (e.g. Copilot, Claude) to improve productivity