Data Engineer

2 weeks ago

Karachi, Sindh, Pakistan Xynotech Full time 1,200,000 - 3,600,000 per year

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


• 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 Tas

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