Principal Data Engineer
- Competitive Salary
- 10% bonus
- 6% pension contribution
- Private Medical
- 25 days annual leave
- Access to our comprehensive flexible benefits including discounts on big brands, wellness and employee assistance programmes, gymflex, buy and sell annual leave, travel and dental insurance
- Work. Life. Smarter. Our commitment to a flexible and hybrid working culture
- Design and deliver enterprise-scale data architectures on AWS using services like S3, EMR, Glue, Redshift, Lambda, and IAM.
- Build and manage robust ETL/ELT pipelines supporting both batch and real-time data ingestion and transformation.
- Deploy and optimise Apache Spark jobs, leveraging Databricks and Delta Lake for distributed data processing.
- Lead the implementation of unified analytics workflows , integrating Databricks with the wider AWS environment.
- Write clean, efficient, and reusable code in Python , building production-ready data transformation scripts.
- Develop complex SQL queries across multiple RDBMS and cloud-native warehouses.
- Drive data quality , lineage , and governance standards across structured and unstructured datasets.
- Collaborate with data scientists, analysts, and business stakeholders to define and deliver scalable solutions.
- Provide technical mentorship and thought leadership to data engineers and wider delivery teams.
- Promote automation and operational efficiency through CI/CD, containerisation (e.g. Docker/ECS), and infrastructure as code.
- Python, SQL, PySpark, Scala, Java
- AWS (S3, Glue, Redshift, Lambda, EMR, IAM, ECS, SageMaker), Databricks, Delta Lake
- Apache Spark, Airflow, Dagster, Rundeck
- Kafka, Logstash, NiFi
- PostgreSQL, Oracle DB, MongoDB
- ELK Stack (Elasticsearch, Logstash, Kibana), Dynatrace, CloudWatch
- GitLab, CI/CD, Docker, Infrastructure as Code
- Agile/Scrum
- Senior/principal data engineering roles with hands-on leadership experience.
- Proven success in designing and deploying cloud-native data solutions, particularly on AWS .
- Advanced experience with Apache Spark , Databricks , and real-time data processing.
- Strong capability in writing and optimising complex SQL and Python code.
- Background in handling large-scale data transformations and integrating multiple data sources.
- Experience with data lakes , Delta Lake , and modern analytics platforms .
- Skilled in stakeholder engagement, mentoring engineers, and delivering high-quality solutions in fast-paced environments.
- A passion for simplifying complex problems and building future-proof data infrastructure.
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