Sr. Data Engineer

Mandatory Technical Skills

• Python - strong handson experience in enterprisescale development
• Apache Spark / PySpark - building largescale 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)

At Zensar, we're "experience-led everything". We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we're a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

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

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and PySpark
• Build and optimize batch and nearrealtime data processing workflows
• Work on GCPbased data platforms, integrating multiple structured and semistructured 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 errorhandling within data pipelines
• Ensure adherence to enterprise data governance, security, and compliance standards
• Support production deployments and provide L2/L3 support as needed