Senior Big Data Engineer

4 hours ago

Bengaluru, Karnataka, India Guide&Bridge Full time US$ 1,50,000 - US$ 2,00,000 per year

Job Title: Senior Big Data Engineer

Experience Required: 3+ Years

About the Role

We are looking for an experienced
Senior Big Data Engineer
to design, build, and optimize large-scale data pipelines and platforms. The ideal candidate will have strong expertise in distributed data processing, cloud-based data solutions, and a proven ability to work with complex datasets to deliver high-performance and scalable systems.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL workflows.
  • Work with structured and unstructured data from multiple sources.
  • Optimize performance of big data solutions for speed and efficiency.
  • Collaborate with Data Scientists, Analysts, and Product teams to enable data-driven decision-making.
  • Implement best practices for data security, governance, and quality.
  • Mentor junior engineers and contribute to architectural decisions.
  • Evaluate and recommend new tools/technologies in the big data ecosystem.

Required Skills & Qualifications

  • Bachelor's or Master's in Computer Science, Information Technology, or related field.
  • 6–10 years of experience in Big Data engineering roles.
  • Strong programming skills in
    Python, Java, or Scala
    .
  • Hands-on experience with
    Big Data frameworks
    – Hadoop, Spark, Hive, Kafka, Flink, etc.
  • Expertise in building ETL pipelines and data ingestion frameworks.
  • Solid understanding of data modeling, warehousing concepts, and SQL/NoSQL databases (Cassandra, HBase, MongoDB).
  • Experience with
    cloud platforms
    (AWS, GCP, or Azure – EMR, Dataproc, HDInsight, Databricks).
  • Strong knowledge of CI/CD and data pipeline orchestration tools (Airflow, Luigi, Oozie).
  • Ability to handle large-scale datasets with a focus on performance and reliability.

Good to Have

  • Experience with
    real-time data streaming
    and event-driven architectures.
  • Familiarity with containerization and orchestration (Docker, Kubernetes).
  • Exposure to Data Lake and Data Mesh architectures.
  • Knowledge of data security, compliance, and governance frameworks.

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