Data Engineer

About the role

We are looking for a Data Engineer to design and maintain cloud‑native data solutions that boost operational efficiency, support regulatory reporting, and deliver actionable insights for our healthcare clients. The role focuses on building scalable pipelines and validation workflows across diverse datasets.

Key responsibilities

• Design, develop, and maintain ETL/ELT pipelines using relational databases, flat files, APIs, and cloud sources.
• Collaborate with backend and architecture teams to define data transformation flows for dashboards and reporting applications.
• Design and optimise data schemas for performance, integrity, and reporting compatibility.
• Write efficient, testable, and reusable data processing scripts in Python and SQL.
• Implement data quality checks, document data lineage, and support pipeline operations across DEV, VAL, and PROD environments.
• Contribute to CI/CD workflows and automation for rapid, secure deployment of data services.
• Maintain data documentation, including metadata, data dictionaries, and technical guides.

Required profile

• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field.
• 4+ years of experience in data engineering, pipeline development, or ETL/ELT roles.
• Strong proficiency in SQL, data transformation logic, and performance tuning for large datasets.
• Experience with version control and CI/CD practices such as GitHub Actions or Jenkins.

Required skills

• Python (including Pandas, PySpark, NumPy)
• SQL
• AWS services: Glue, EMR, Step Functions, Lambda, S3, Aurora, SNS, CloudFormation/CDK
• Distributed computing: Hadoop, Spark
• Data orchestration frameworks
• Snowflake, Amazon RDS
• Data transformation tools: dbt, Dataform