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Senior Bigdata Engineer
Senior Bigdata EngineerIris Software Inc. • Whippany, NJ, United States
Senior Bigdata Engineer

Senior Bigdata Engineer

Iris Software Inc. • Whippany, NJ, United States
[job_card.variable_hours_ago]
[job_preview.job_type]
  • [job_card.temporary]
[job_card.job_description]

Greetings!

We are looking for a Big Data Engineer to design, build, and maintain scalable data solutions. This role focuses on developing reliable data pipelines and platforms that support analytics, reporting, and data-driven decision making. The ideal candidate has strong hands-on experience with Python and SQL and is comfortable working with large, complex datasets.

Position : Sr. Big Data Engineer

Location : Whippany NJ (Hybrid)

Contract : Long term contract

Client : One of the largest financial clients.

Responsibilities

  • Design, develop, and maintain large-scale data pipelines and data platforms
  • Build efficient ETL and ELT processes using Python and SQL
  • Optimize data models, queries, and workflows for performance and reliability
  • Work with structured and unstructured data from multiple sources
  • Collaborate with data scientists, analysts, and software engineers to support analytics and machine learning use cases
  • Ensure data quality, consistency, and availability across systems
  • Monitor and troubleshoot data pipelines in production environments
  • Document data processes, models, and best practices

Required Qualifications

  • Strong experience in Python for data processing and pipeline development
  • Advanced SQL skills, including query optimization and complex data transformations
  • Experience working with big data technologies such as Spark, Hadoop, or similar frameworks
  • Solid understanding of data modeling, warehousing, and lakehouse concepts
  • Experience with cloud data platforms (AWS, Azure, or Google Cloud)
  • Familiarity with version control systems such as Git

    • Preferred Qualifications

  • Experience with workflow orchestration tools such as Airflow or similar
  • Knowledge of streaming technologies such as Kafka or equivalent
  • Experience with containerization and deployment tools (Docker, Kubernetes)
  • Exposure to data governance, security, and compliance best practices

    • Best Regards,

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