Data Engineer

We’re looking for a hands-on Data Engineer to join our team and lead the development of robust data pipelines powering the IllumiFi Analytics platform. You’ll work with cutting-edge, cloud-native tools to architect, implement, and optimize serverless data solutions on AWS.

If you enjoy working with Python, PySpark, and modern data lakehouse patterns in a fast-paced environment — this is your opportunity to build impactful solutions from the ground up.

What You’ll Actually Do Here

• Design and implement scalable, serverless data pipelines using AWS services such as Glue, Lambda, Step Functions, Athena, and S3
• Build and optimize ETL processes using Python/PySpark for efficient data transformations
• Ingest and process structured and semi-structured data formats including JSON, Parquet, and CSV
• Integrate with external APIs using REST protocols and OAuth2 authentication
• Model analytical datasets with star/snowflake schemas, implement SCD Type 2, and define partitioning strategies for efficient query performance
• Build and maintain a well-organized S3-based data lake structure to support analytics workloads
• Apply best practices for version control, data quality, and automation using GitHub workflows
• Drive technical design discussions and contribute to improving infrastructure, tooling, and data processes

What We’re Looking For

• 2+ years of experince in Data Engineering

Strong hands-on experience with AWS services — especially Glue, Lambda, S3, Step Functions, and Athena

• Solid command of Python/PySpark for building and managing ETL pipelines
• Proven track record working with large-scale datasets and optimizing performance
• Deep understanding of data modeling, transformations, and SQL for analytical use cases
• Familiarity with REST APIs, OAuth2 authentication, and data integration patterns
• Experience with Git, CI/CD, and workflow automation
• A problem-solving mindset and a passion for scalable, efficient data engineering
• Ability to work independently and collaborate across teams

Tools & Platforms

• Languages & Frameworks: Python, PySpark
• Cloud & Tools: AWS Glue, Lambda, S3, Step Functions, Athena
• Data Formats: JSON, Parquet, CSV
• Modeling & Querying: SQL, Star/Snowflake schemas
• Version Control: Git, GitHub workflows

Nice-to-Haves

• Experience with Apache Iceberg or Hudi for data lakehouse architectures
• Knowledge of data quality frameworks like Great Expectations
• Familiarity with Terraform/IaC for infrastructure automation
• Background in e-commerce or analytics platforms
• Exposure to performance tuning for large data workloads
• Hands-on with Step Functions HTTP Task

Job Type: Full-time

Education:

• Bachelor's (Required)

Experience:

• Data Engineering: 2 years (Required)

Location:

• Karachi (Required)

Work Location: In person