Data Engineer
On-siteLahore, Punjab, Pakistan
Job Summary
Design, build, and maintain scalable ETL/ELT pipelines on AWS, ingesting and transforming data from multiple source systems into the organization's data warehouse. Write, optimize, and maintain complex SQL queries to develop reliable data models supporting BI dashboards, reporting, and business analysis. Orchestrate workflows using Apache Airflow or AWS Step Functions while monitoring pipeline health, investigating failures, and implementing long-term solutions for recurring issues. Collaborate closely with the BI team to improve data accuracy, establish feedback loops to address quality gaps, and enhance pipeline reliability, performance, observability, and cost efficiency. Use AI-assisted development tools to accelerate iteration and maintain technical documentation for all pipelines and workflows.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline.
- 2–3 years of professional experience in data engineering or a backend/software engineering role involving significant data work.
- Strong SQL skills, including experience writing and optimizing complex queries.
- Proficiency in Python for building data pipelines and automation workflows.
- Hands-on experience with AWS data services such as S3, Glue, Redshift, Lambda, Athena, and EventBridge.
- Practical experience with Apache Airflow or AWS Step Functions for workflow orchestration.
- Strong understanding of data-modelling fundamentals, including normalization and dimensional modelling.
- Familiarity with Git and collaborative software-development workflows.
- Ability to troubleshoot data-quality issues, pipeline failures, and performance bottlenecks.
- Strong analytical, problem-solving, and cross-functional communication skills.
- Willingness to work onsite in Lahore from 11:00 AM to 8:00 PM PKT.
Desired Qualifications
- Experience with dbt for SQL-based data transformation.
- Familiarity with Terraform or other infrastructure-as-code tools.
- Experience with CI/CD pipelines using GitHub Actions, AWS CodePipeline, or similar tools.
- Experience with data monitoring, observability, and pipeline-cost optimization.
- Familiarity with AI coding assistants such as Claude Code.
- Understanding of data governance, validation, and quality-control practices.
- Interest in growing into broader backend or software engineering responsibilities.
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