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Data Engineer -Python & Kafka

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Onsite

Data Engineer -Python & Kafka

Tata Consultancy Services

Data Engineer -Python & Kafka

Skills

Google Cloud PlatformSQL QueriesData EngineeringDockerPythonKafkaAWSKubernetesPySparkApache AirflowComplianceAzure

20 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

29 September 2026

What they need


Role: Data Engineer Python & Kafka
Experience: 6-10 Years
Locations: Chennai, Bengaluru, Hyderabad, Pune, Kochi, Kolkata, NCR/Delhi

Virtual Interview: 01-OCT-26

Job Summary

We are looking for an experienced Data Engineer with strong expertise in Python and Apache Kafka to design, develop, and maintain scalable data pipelines and real-time data processing solutions. The ideal candidate should have experience working with large-scale data platforms, distributed systems, and cloud-based data engineering environments.

Key Responsibilities

  • Design, develop, and optimize batch and real-time data pipelines using Python.
  • Build and maintain Kafka-based streaming solutions for high-volume data processing.
  • Develop scalable ETL/ELT frameworks and data ingestion pipelines.
  • Integrate data from multiple sources and ensure data quality, reliability, and consistency.
  • Work closely with Data Scientists, Analysts, and Application Development teams to support data requirements.
  • Implement monitoring, logging, and performance tuning for data pipelines.
  • Participate in architecture discussions and recommend best practices for data engineering solutions.
  • Ensure compliance with data governance and security standards.

Required Skills

  • Strong experience in Python programming.
  • Hands-on experience with Apache Kafka, Kafka Streams, Kafka Connect, and message-based architectures.
  • Experience in building ETL/ELT pipelines.
  • Strong understanding of SQL and database concepts.
  • Experience with distributed data processing frameworks such as Spark is preferred.
  • Knowledge of REST APIs and data integration.
  • Experience with cloud platforms such as GCP, AWS, or Azure.
  • Familiarity with CI/CD, Git, and DevOps practices.
  • Strong problem-solving and analytical skills.

Preferred Skills

  • Experience with PySpark.
  • Knowledge of Airflow or other workflow orchestration tools.
  • Exposure to Data Lake/Data Warehouse architectures.
  • Understanding of containerization technologies such as Docker and Kubernetes.

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