Sr. Data Engineer

Mandatory Technical Skills

• Python – strong hands‑on experience in enterprise‑scale development
• Apache Spark / PySpark – building large‑scale distributed data pipelines
• Big Data concepts – partitioning, shuffling, performance tuning
• SQL – complex queries, joins, and optimization
• Cloud exposure on GCP, including:
  • BigQuery
  • Cloud Storage (GCS)
  • Dataflow (preferred)
  • Pub/Sub (basic understanding)
• Experience working with large datasets (TB scale)

Responsibilities

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and PySpark
• Build and optimize batch and near‑real‑time data processing workflows
• Work on GCP‑based data platforms, integrating multiple structured and semi‑structured data sources
• Develop data transformations, validations, and enrichment logic aligned to business requirements
• Optimize Spark jobs for performance, scalability, and cost efficiency
• Collaborate with data architects, platform teams, and downstream consumers
• Implement logging, monitoring, and error‑handling within data pipelines
• Ensure adherence to enterprise data governance, security, and compliance standards
• Support production deployments and provide L2/L3 support as needed

Qualifications

 

Good to Have / Preferred Skills

• Knowledge of Kafka or other messaging systems
• Experience with Airflow / Cloud Composer
• Containerization and orchestration exposure (Docker / Kubernetes)
• CI/CD exposure for data pipelines
• Familiarity with data warehousing and analytics use cases
• Prior experience in financial services / regulated environments

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