Data Engineer

We’re looking for a Data Engineer / Analytics Engineer who can design, build, and optimize scalable data pipelines on cloud platforms and work closely with business teams to turn raw data into reliable, analytics-ready insights.

Key Responsibilities

• Design and maintain Spark/PySpark-based ETL pipelines for high-volume batch and incremental data processing

• Build and manage AWS Glue Jobs, Glue Crawlers, and S3-based data lake ingestion

• Develop dimensional and fact-dimension models and maintain curated data marts using Redshift/Athena

• Optimize SQL and Spark SQL queries for better performance and efficiency

• Drive cloud cost optimization across storage, compute, and query usage using AWS Cost Explorer and CUR analysis

• Build and maintain BI dashboards for revenue, engagement, and operational reporting

• Handle ad-hoc data requests and convert business requirements into optimized queries and temporary data models

• Collaborate with Product, Business, and Analytics teams on data structures, reporting, and KPI definitions

Required Skills

• 2+ years of hands-on experience with Python, SQL, and Spark SQL/PySpark

• Strong experience with AWS S3, Redshift, Athena, Glue, and CloudWatch

• Good understanding of Data Warehousing and Dimensional Modeling

• Strong knowledge of Partitioning, Indexing, and Query Optimization

• Experience with BI/Analytics tools such as Metabase, Matomo, or similar platforms

• Proven experience in improving data pipeline performance and/or optimizing cloud costs

⭐ Nice to Have

• Experience in OTT/Streaming Media Analytics or Insurance/BFSI domains

• Experience with incremental data processing and near real-time pipelines

• Publications or applied research in Data Engineering

If you enjoy building scalable data solutions, solving complex data problems, and working with modern AWS data technologies, we’d love to hear from you!

Interested candidates are welcome to apply or share their updated CV at: [email protected]