Lead Data Engineer

Location: Gulberg 3 Lahore
Work Mode: On-site Full-Time
Experience:7 Years

Were looking for a Lead Data Engineer to own and scale the end-to-end data infrastructure that powers marketing monetization and analytics across our gaming portfolio.

Youll design build and optimize data pipelines that integrate data from Adjust ad network APIs and in-game sources into our data stack. As a team leader youll set the technical direction establish best practices and mentor other engineers to build reliable scalable data systems. Youll also help shape how the team adopts AI-assisted and agentic development in its daily workflows.

• Lead the architecture design and optimization of our data platform (AWS Iceberg StarRocks).
• Own the platforms infrastructure as code. Provision and manage AWS resources (S3 Glue Lambda EC2 EBS ECS Network Load Balancers IAM and networking) along with data platform components using Terraform and modular peer-reviewed version-controlled configurations.
• Deploy and operate self-hosted platform services such as StarRocks Apache Superset and Airflow on EC2 and ECS. This includes EBS storage sizing and performance optimization Network Load Balancer configuration high availability scaling and cost optimization.
• Design and manage GitLab CI/CD pipelines for data pipelines dbt models and Terraform code covering automated testing schema validation plan/apply workflows and controlled promotion across environments.
• Build and maintain ETL/ELT pipelines that ingest data from:
  • Mobile Measurement Partners (MMPs) such as Adjust
  • Ad network APIs (Meta Google Ads AppLovin Unity Ads IronSource etc.
  • Monetization and in-app purchase data sources
• Define and enforce data engineering best practices including testing code reviews version control documentation and release management.
• Drive the teams adoption of agentic development by establishing conventions for using AI coding agents (e.g. Claude Code Cursor and GitHub Copilot) to scaffold pipelines generate tests refactor code and write documentation ensuring human review of every change before deployment.
• Collaborate with analysts data scientists and marketing teams to design performant data models and enable self-service reporting through Apache Superset.
• Establish a data roadmap focused on scalability cost efficiency and reliability.
• Implement data observability alerting and performance monitoring.
• Mentor and support junior data engineers while promoting high engineering standards.

• 7 years of experience in data engineering or related roles.
• Bachelors degree in a STEM field (Computer Science Engineering Mathematics or a related discipline).
• Strong expertise in:
  • AWS (S3 Glue Lambda Athena EC2 EBS ECS and Network Load Balancer)
  • Apache Iceberg or similar lakehouse technologies (Delta Lake Hudi)
  • StarRocks / CelerData ClickHouse or similar MPP systems
• Hands-on experience with Terraform or a similar infrastructure-as-code tool (CloudFormation Pulumi) including managing state modules and multiple environments.
• Proven experience building and maintaining CI/CD pipelines ideally using GitLab CI/CD for both data and infrastructure code.
• Proficiency in Python for data processing and API integration.
• Strong SQL and data modeling skills.
• Hands-on experience integrating marketing and ad network APIs.
• Familiarity with Airflow dbt or other orchestration and transformation tools.
• Familiarity with agentic development including practical experience using AI coding agents in daily workflows and sound judgment about where they can accelerate delivery and where their output requires careful review.
• Strong communication leadership and cross-functional collaboration skills.

• Experience with real-time streaming technologies (Kafka Flink Kinesis).
• Experience with Apache Superset including dashboard development performance tuning and administration or with other BI tools (Power BI Looker DataLens).
• Experience in gaming analytics user acquisition or pLTV modeling.
• Experience setting up shared agentic tooling for a team such as context and prompt conventions custom agent workflows or MCP integrations with internal systems.
• Experience with Docker and Kubernetes-based orchestration (EKS).