Job Description

Design, develop, and maintain scalable, high-performance data pipelines and ETL processes.
Work with GCP services such as BigQuery, Dataflow, Dataproc, and Cloud Storage to manage and process large datasets.
Utilize PySpark to build distributed data processing workflows.
Write efficient, optimized SQL queries for data extraction, transformation, and loading.
Collaborate with cross-functional teams including Data Scientists, Analysts, and Product Owners to deliver business-critical data solutions.
Ensure data quality, integrity, and security across all processes.
Participate in performance tuning, troubleshooting, and optimization of big data workflows.

Required Skills & Experience:

Minimum 12 years of professional experience in Data Engineering.
Strong hands-on expertise in GCP, PySpark, Python, and SQL.
Proven track record in building enterprise-scale data platforms.
Strong understanding of data modeling, ETL concepts, and data warehouse design.
Experience working in retail or e-commerce domain (preferred).
Excellent problem-solving, communication, and collaboration skills.

Nice to Have:

Apptad

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