Overview
The Senior Data Engineer will play a key role in building reliable and scalable data products that drive significant business value. Working within a collaborative environment alongside architects, analysts, and data scientists, the contractor will design and maintain modern cloud-based data platforms while addressing complex engineering challenges. This position emphasizes the importance of creating effective data solutions that support analytics and operational decision-making, all while benefitting from a flexible, hybrid working pattern.
Responsibilities
- Design, build, and maintain scalable data products and pipelines.
- Own solutions from requirements gathering through to deployment and monitoring.
- Develop cloud-native data platforms using modern engineering practices.
- Improve platform performance, resilience, security, and cost efficiency.
- Implement data quality, observability, and governance controls.
- Collaborate with stakeholders to translate business requirements into technical solutions.
- Contribute to CI/CD, infrastructure-as-code, and automation initiatives.
- Mentor engineers and champion data engineering best practices.
Requirements
- Strong software engineering fundamentals including Python, Scala or Java, SQL, Git, testing, APIs, and CI/CD.
- Experience building modern cloud-based data platforms within AWS, Azure, or GCP.
- Strong knowledge of technologies such as Databricks, Snowflake, Spark, Kafka, dbt, Airflow, or Azure Data Factory.
- Experience designing and delivering end-to-end data engineering solutions.
- Understanding of distributed computing, data partitioning, optimization, and large-scale data processing.
- Production mindset with experience in monitoring, security, data quality, resilience, and operational support.
- Ability to balance technical excellence with pragmatic decision-making.
- Experience developing lakehouse or modern data warehouse architectures is desirable.