Description

Architect and lead the migration of large-scale data systems from on-premises environments to Google Cloud Platform.

Responsibilities

• Design and implement scalable data solutions on GCP, serving as the target architecture for migrated workloads.
• Develop reusable frameworks, templates, and code libraries to standardize data engineering workflows and accelerate delivery.
• Lead the migration of data and processes from Teradata and Hadoop to BigQuery, GCS, Dataflow, and Dataproc.
• Translate complex legacy ETL logic from Informatica and Teradata into modern, cloud-native pipelines using Python and SQL.
• Optimize BigQuery performance through partitioning, clustering, and query tuning while ensuring data integrity and governance.

Required Skills

• 10+ years of professional experience in data engineering or architecture roles.
• Deep expertise with Teradata architecture, utilities (BTEQ, TPT), and advanced SQL/Stored Procedure development.
• Hands-on experience with Hadoop ecosystem (HDFS, YARN, Hive) and PySpark for large-scale data processing.
• Strong proficiency in Google Cloud Platform services including BigQuery, Cloud Storage, Dataflow, and Dataproc.
• Expert-level SQL skills, including complex joins, window functions, and performance tuning.
• Strong programming skills in Python with a focus on software engineering best practices.
• Experience designing and building reusable data engineering frameworks for ingestion, transformation, and validation.
• Knowledge of enterprise ETL tools like Informatica PowerCenter.

Key Skills

Education

Any Graduate