Principal Architect

2 days ago

Tiruppur, Tamil Nadu, India beBeeDataEngineer Full time ₹ 1,80,00,000 - ₹ 2,00,00,000

We are seeking a skilled Big Data Engineer with expertise in Scala, Spark, Python, NiFi, and Apache Kafka to join our data engineering team.

The ideal candidate will have a proven track record in building, scaling, and optimizing big data pipelines, and hands-on experience in distributed data systems and cloud-based solutions.

Key Responsibilities:

  • Design, develop, and optimize large-scale data pipelines and distributed data processing systems.
  • Work extensively with Scala, Spark (PySpark), and Python for data processing and transformation.
  • Develop and integrate streaming solutions using Apache Kafka and orchestration tools like NiFi / Airflow.
  • Write efficient queries and perform data analysis using Jupyter Notebooks and SQL.
  • Collaborate with cross-functional teams to design scalable cloud-based data architectures.
  • Ensure delivery of high-quality code through code reviews, performance tuning, and best practices.
  • Build monitoring and alerting systems leveraging Splunk or equivalent tools.
  • Participate in CI/CD workflows using Git, Jenkins, and other DevOps tools.
  • Contribute to product development with a focus on scalability, maintainability, and performance.

Mandatory Skills:

  • Scala: Minimum 3+ years of hands-on experience.
  • Strong expertise in Spark (PySpark) and Python.
  • Hands-on experience with Apache Kafka.
  • Knowledge of NiFi / Airflow for orchestration.
  • Strong experience in Distributed Data Systems (5+ years).
  • Proficiency in SQL and query optimization.
  • Good understanding of Cloud Architecture.

Preferred Skills:

  • Exposure to messaging technologies like Apache Kafka or equivalent.
  • Experience in designing intuitive, responsive UIs for data analytics visualization.
  • Familiarity with Splunk or other monitoring/alerting solutions.
  • Hands-on experience with CI/CD tools (Git, Jenkins).
  • Strong grasp of software engineering concepts, data modeling, and optimization techniques.

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