Senior Data Engineer

1 week ago

Gurgaon, Haryana, India ORION SYSTEMS Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Work Location : Gurugram - Hybrid

Notice : Immediate to short notice

Experience : 7+ years

Required skills and experience

  • Proven experience in working with GA4 data, including understanding its data model, event-based tracking, and integration with BigQuery.
  • 6+ years of hands-on experience with Google BigQuery or Snowflake including advanced SQL techniques (CTEs, window functions, aggregate functions), schema design, and performance optimization.
  • 6+ years of hands-on experience with advanced SQL techniques (CTEs, window functions, aggregate functions).
  • 5+ years of strong experience in Python programming (object-oriented/functional programming, Pandas, PySpark).
  • 5+ years working with cloud platforms.
  • Experience designing star schemas, analyzing data warehouses, and applying data warehouse methodologies, particularly in the context of digital analytics data.
  • Essential experience in loading data into warehouse/ODS environments from diverse sources and formats. Design strategies for new data ingestion requests, including logical and physical data modeling.
  • Hands-on experience with version control and CI/CD pipelines for data engineering workflows.
  • Proven ability to perform unit testing (SQL scripts, ETL modules), integration testing, and performance/load/stress testing.

Roles & Responsibility:

  • Design, build, and deploy robust ETL and data management processes specifically for ingesting, transforming, and loading high-volume digital analytics data from Google Analytics 4 (GA4) into BigQuery/Snowflake.
  • Develop and optimize BigQuery/Snowflake datasets, tables, and views to support various analytical needs, ensuring efficient querying and data integrity.
  • Design, build, and deploy ETL job workflows with reliable error/exception handling and rollback frameworks. This includes designing and implementing data pipelines to feed data models for subsequent consumption.
  • Monitoring and optimizing data processing and storage resources, with a focus on performance and cost efficiency.
  • Troubleshooting and resolving data pipeline issues and performance bottlenecks, particularly those related to large-scale digital data processing.
  • Write complex, customized SQL queries to manipulate data, generate automatic periodic reports, and support ad-hoc analytical requests.
  • Build applications and scripts using Python to automate data processes, integrate systems, and enhance data quality.

Interested candidates can mail me your resume to

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