Overview
The role of Senior Data Engineer involves collaborating with a team of architects, analysts, and engineering teams to build and enhance modern data platforms that create significant business value. The contractor will focus on designing and maintaining scalable data products, implementing robust engineering practices, and influencing architecture and strategy within a flexible, hybrid work environment. This 12-month engagement offers an opportunity to work on large-scale data and cloud transformation initiatives.
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.