Location: London, England, United Kingdom
Job Type: Full Time
Employment Type: Permanent
Experience Level: Senior
Senior Data Engineer
We are seeking a highly skilled Senior Data Engineer to design, develop, and optimize the enterprise data platforms that power analytics, reporting, automation, and data-driven decision-making. This role will be central to creating reliable, scalable, and secure data products that enable teams across the organization to access trusted information when they need it.
As a Senior Data Engineer, you will work in partnership with data architects, software engineers, analysts, data scientists, product managers, and business stakeholders to translate complex requirements into robust data solutions. You will lead the development of modern data pipelines, integration services, data models, and observability capabilities across cloud and on-premises environments. The successful candidate will combine strong hands-on engineering expertise with a practical understanding of data governance, quality, performance, and security. You will influence technical standards, improve engineering practices, mentor colleagues, and help shape the future of the organization’s data ecosystem. This is an opportunity to solve complex technical challenges and deliver data capabilities that create measurable value across a large enterprise.
Key Responsibilities
- Design, build, deploy, and maintain scalable data pipelines, integration services, and reusable data products.
- Develop batch, streaming, and near-real-time data-processing solutions to support analytical and operational requirements.
- Create and optimize data models, schemas, and storage structures for data warehouses, data lakes, and lakehouse platforms.
- Partner with stakeholders to define data requirements, source-system dependencies, quality expectations, and delivery priorities.
- Integrate data from enterprise applications, APIs, cloud platforms, databases, files, and third-party systems.
- Implement automated data-quality controls, validation rules, reconciliation processes, and monitoring to maintain trusted data.
- Optimize data ingestion, transformation, orchestration, and query performance across high-volume and complex data sets.
- Apply data governance, lineage, metadata, retention, privacy, and access-control requirements throughout the data lifecycle.
- Establish CI/CD processes, automated testing, version control, and deployment standards for data engineering solutions.
- Monitor production data services, investigate incidents, and resolve pipeline failures, data defects, and performance issues.
- Collaborate with analytics and data science teams to deliver accessible, well-documented, and fit-for-purpose data sets.
- Conduct code reviews and promote engineering standards, reusable components, documentation, and operational best practices.
- Mentor data engineers and contribute to the development of technical capability across the wider data organization.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Engineering, or a related technical discipline; equivalent experience may be considered.
- Seven or more years of professional experience in data engineering, software engineering, analytics engineering, or a related field.
- Strong proficiency in SQL and one or more programming languages, including Python, Scala, Java, or Spark SQL.
- Demonstrated experience building and supporting enterprise-scale ETL, ELT, streaming, and data-integration pipelines.
- Experience with cloud data platforms such as AWS, Microsoft Azure, Google Cloud Platform, Snowflake, Databricks, or BigQuery.
- Strong knowledge of distributed data-processing technologies, including Apache Spark, Kafka, Flink, Hadoop, or similar frameworks.
- Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, dbt, Prefect, Dagster, or comparable platforms.
- Proficiency with relational and non-relational databases, including PostgreSQL, SQL Server, Oracle, MongoDB, Cassandra, or similar technologies.
- Strong understanding of data warehousing, dimensional modeling, data lakes, lakehouse architecture, and data mesh concepts.
- Experience implementing data quality, cataloging, lineage, observability, and governance capabilities.
- Familiarity with DevOps and infrastructure-as-code practices using Git, CI/CD pipelines, Docker, Kubernetes, Terraform, or similar tools.
- Knowledge of data security, privacy, encryption, identity and access management, and secure data-handling principles.
- Strong analytical, problem-solving, communication, documentation, and stakeholder-management skills.
- Certifications such as AWS Certified Data Engineer, Microsoft Azure Data Engineer Associate, Google Professional Data Engineer, SnowPro, or Databricks certification are preferred.
- Authorization to work in the United Kingdom is required.
Equal Opportunity Employer
We are committed to providing equal employment opportunities to all applicants and employees. Qualified candidates will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected under applicable federal, state, or local law.
Job Type: Full Time, Permanent
Pay: £90,000.00-£95,000.00 per year
Benefits:
- Canteen
- Free parking
- Gym membership
- On-site gym
- On-site parking
Work Location: In person
