Data Engineer

Zensar Technologies

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Gurugram, Haryana, IndiaFresher1 month ago
RoleData Engineer
LocationGurugram, Haryana, India
ExperienceFresher
QualificationB.E / B.Tech / MCA / M.Tech

Job Description

  • As a Data Engineer at Zensar, you will design, develop, and maintain scalable data pipelines using Python and PySpark . You will be responsible for building both batch and near-real-time data processing workflows on Google Cloud Platform (GCP) . Your role involves integrating multiple structured and semi-structured data sources, applying complex transformations, and ensuring data enrichment logic aligns with business goals.
  • A significant part of your role will focus on Big Data optimization . You will tune Spark jobs for maximum performance, scalability, and cost efficiency while managing datasets at the Terabyte (TB) scale. Collaborating with data architects and platform teams, you will implement logging, monitoring, and error-handling protocols. This position offers a deep dive into enterprise data governance and security standards within a highly regulated environment.

Key Responsibilities

  • Design and maintain scalable data pipelines using Python and PySpark .
  • Build and optimize data processing workflows on GCP (BigQuery, Dataflow, GCS) .
  • Integrate diverse data sources and develop complex transformation logic.
  • Perform Spark performance tuning (partitioning, shuffling, and caching).
  • Collaborate with cross-functional teams to deliver end-to-end data solutions.
  • Implement logging, error-handling, and monitoring within pipelines.
  • Ensure compliance with enterprise data governance and security standards.
  • Support production deployments and provide technical support as needed.

Skills & Eligibility

  • Education: B.E/B.Tech or equivalent in Computer Science or Information Technology.
  • Programming: Strong hands-on experience in Python development.
  • Big Data: Proficiency in Apache Spark / PySpark and distributed computing concepts.
  • Cloud: Exposure to GCP services including BigQuery, Cloud Storage, and Pub/Sub .
  • SQL: Ability to write and optimize complex SQL queries and joins.
  • Data Scale: Familiarity with handling large-scale datasets (TB scale).
  • Good to Have: Knowledge of Airflow , Kafka, Docker, or Kubernetes.
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