Job & Role Description:
The Data Engineer will work on an end-to-end data layer, owning data ingestion, transformation, and analytics enablement. The role requires close collaboration with client teams to integrate multiple source systems via APIs and custom services, debug and enhance existing integration code, and propose improved data pipeline designs when required.
The engineer will be responsible for building and maintaining robust ETL/ELT pipelines using dbt and AWS-native services, ensuring reliable movement of data across source, staging, and analytical schemas. In addition, the role includes enabling business intelligence by integrating processed data with Microsoft Power BI, understanding customer reporting requirements, and supporting the design of meaningful dashboards and visualizations.
This position requires strong analytical thinking, adaptability, and clear communication with both technical and non-technical stakeholders.
Skills Required / Key Requirements:
- Strong fundamentals in data engineering, data modeling, and cloud-based analytics architectures.
- Proficiency in SQL, Python, and familiarity with C# for integration and debugging purposes.
- Experience with ETL/ELT frameworks, dbt, and orchestration using Airflow/DAGs.
- Hands-on experience with AWS data services, cloud security concepts, and configuration management.
- Working knowledge of Microsoft Power BI, including data modeling, measures, and visualization best practices.
- Ability to translate business and client requirements into data models and analytical visualizations.
- Strong analytical, problem-solving, and debugging skills.
- Excellent communication skills, with the ability to collaborate effectively with clients and cross-functional teams.
Tech Specific Experience:
Strong experience with AWS Cloud Services including AWS Redshift, AWS S3, AWS Secrets Manager, and AWS Managed Workflows for Apache Airflow (MWAA). Hands-on experience building and debugging data integrations using APIs and services implemented in Python and/or C#. Proven experience designing and executing ETL/ELT pipelines using dbt and standard data engineering best practices. Expertise in SQL for complex query writing, schema transformations (source → staging → model → data marts), and performance optimization on cloud data warehouses. Experience integrating data models with Microsoft Power BI, including dataset modeling and refresh strategies.
Location: Lahore