Data Engineer – Turn Complexity into Clarity

About the role

We are seeking a Data Engineer who enjoys turning complex data challenges into clear, actionable solutions. In this role you will enable data‑driven decision‑making by building and maintaining high‑performance data products for our clients.

Key responsibilities

• Design, develop and optimise data pipelines on AWS using services such as S3, Glue, Redshift and Spark.
• Implement data ingestion, transformation and orchestration workflows with AWS Glue Ingestion Framework, Airflow, DBT and Control‑M.
• Maintain and query data lakes and lakehouses, ensuring data quality and governance.
• Collaborate with cross‑functional teams to integrate REST APIs and event‑driven architectures using Kafka.
• Monitor, log and troubleshoot pipelines using CloudWatch, Grafana, Splunk and other observability tools.

Required profile

• 5‑8 years of professional experience as a Data Engineer.
• Strong proficiency in SQL, stored procedures and relational databases such as PostgreSQL and MS SQL.
• Advanced Python programming skills.
• Hands‑on experience with AWS data services and big‑data processing frameworks.

Required skills

• Amazon S3, AWS Glue Data Catalog, Apache Spark, Amazon Redshift
• AWS Glue Ingestion Framework, Starburst Presto
• Airflow, DBT, Control‑M
• SQL, PostgreSQL, MS SQL
• Python
• CI/CD tools (GitHub Actions, GitLab CI, Bamboo, Bitbucket)
• Infrastructure as Code (CloudFormation)
• Kafka, REST APIs
• Lake Formation, IAM, CloudWatch
• Monitoring tools (Grafana, Splunk)