Lead Data Engineer
Source Group International
Reference: 56862Location: London, United KingdomSalary: 130,000 per annumIndustry: EngineeringOverview We are seeking a Lead Data Engineer to design, build and own scalable data platforms that enable high-quality analytics, reporting and data-driven products.
If you think you are the right match for the following opportunity, apply after reading the complete description.
You will provide technical leadership across the data engineering function, set standards for reliability and governance, and partner with stakeholders to deliver trusted datasets and pipelines.Key Responsibilities Lead the architecture and delivery of modern data platforms (lakehouse/warehouse) and robust ETL/ELT pipelines.Define engineering standards for code quality, testing, documentation, security and operational excellence.Own data modelling (dimensional, Data Vault and domain-oriented approaches) and optimise performance and cost.Implement orchestration, monitoring and alerting for data workflows; manage SLAs and incident response.Drive data governance: lineage, catalogue, access controls, retention policies and GDPR-aligned practices.Collaborate with analytics, software and platform teams to deliver reusable data products and APIs.Mentor engineers, conduct code reviews, and contribute to hiring and capability development.Required Skills & Experience Significant experience in data engineering, including leading teams or major technical initiatives.Expert SQL and strong programming skills in Python and/or Scala.Cloud data engineering experience (AWS, Azure or GCP), including object storage, compute and managed data services.Strong experience with modern data warehousing/lakehouse tools (e.g., Snowflake, BigQuery, Redshift, Databricks).Hands-on orchestration experience (e.g., Airflow, Dagster, Prefect) and CI/CD for data pipelines.Experience with streaming and event-driven data (e.g., Kafka, Kinesis, Pub/Sub) is highly desirable.Proficiency with infrastructure as code (e.g., Terraform, CloudFormation) and containerisation (Docker; Kubernetes beneficial).Strong understanding of data quality frameworks, testing (unit/integration), and observability.Excellent stakeholder management and communication skills, able to translate requirements into technical solutions.Qualifications Bachelor’s degree in Computer Science, Engineering, Mathematics or a related discipline (or equivalent experience).Relevant cloud or data certifications are advantageous.What You’ll Bring A pragmatic, delivery-focused mindset with a commitment to high standards.Ability to lead by example, coach others and build effective engineering practices. xrnqpay Curiosity, accountability and a continuous improvement approach.
If you think you are the right match for the following opportunity, apply after reading the complete description.
You will provide technical leadership across the data engineering function, set standards for reliability and governance, and partner with stakeholders to deliver trusted datasets and pipelines.Key Responsibilities Lead the architecture and delivery of modern data platforms (lakehouse/warehouse) and robust ETL/ELT pipelines.Define engineering standards for code quality, testing, documentation, security and operational excellence.Own data modelling (dimensional, Data Vault and domain-oriented approaches) and optimise performance and cost.Implement orchestration, monitoring and alerting for data workflows; manage SLAs and incident response.Drive data governance: lineage, catalogue, access controls, retention policies and GDPR-aligned practices.Collaborate with analytics, software and platform teams to deliver reusable data products and APIs.Mentor engineers, conduct code reviews, and contribute to hiring and capability development.Required Skills & Experience Significant experience in data engineering, including leading teams or major technical initiatives.Expert SQL and strong programming skills in Python and/or Scala.Cloud data engineering experience (AWS, Azure or GCP), including object storage, compute and managed data services.Strong experience with modern data warehousing/lakehouse tools (e.g., Snowflake, BigQuery, Redshift, Databricks).Hands-on orchestration experience (e.g., Airflow, Dagster, Prefect) and CI/CD for data pipelines.Experience with streaming and event-driven data (e.g., Kafka, Kinesis, Pub/Sub) is highly desirable.Proficiency with infrastructure as code (e.g., Terraform, CloudFormation) and containerisation (Docker; Kubernetes beneficial).Strong understanding of data quality frameworks, testing (unit/integration), and observability.Excellent stakeholder management and communication skills, able to translate requirements into technical solutions.Qualifications Bachelor’s degree in Computer Science, Engineering, Mathematics or a related discipline (or equivalent experience).Relevant cloud or data certifications are advantageous.What You’ll Bring A pragmatic, delivery-focused mindset with a commitment to high standards.Ability to lead by example, coach others and build effective engineering practices. xrnqpay Curiosity, accountability and a continuous improvement approach.
Reference: WJ-799_34461791