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4 Hours ago

Sr. Data Engineer

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3500000 - 4000000 INR - Annual
Pune, Pimpri-chinchwad
10 - 16 Yrs
Information Technology
On-site
Full-Time
Antal International

Overview

As a Senior Staff Software Engineer, you will work closely with the Data Engineering team to design, develop, and maintain distributed data infrastructure, ETL/ELT pipelines, data applications, and integration solutions.
You’ll collaborate with some of the best minds in the industry, tackle complex data problems, and build scalable products from scratch while helping modernize legacy applications.


Qualifications

  • 10–15 years of proven experience in software engineering, with a strong focus on data infrastructure and engineering.

  • Expertise in object-oriented programming (OOP), design patterns, algorithm optimization, and problem-solving from first principles.

  • Hands-on experience with:

    • Unstructured log data and real-time data processing.

    • Distributed computing frameworks and streaming data systems (e.g., Spark, Kafka, Flink).

  • Proficiency in Python; experience with Java or Scala is a strong plus.

  • Deep understanding of data engineering technologies, including:

    • ETL/ELT pipelines

    • Data integration

    • Operational monitoring and data quality assurance

  • Experience in developing Proofs of Concept (POCs) and collaborating across teams to deliver production-ready data solutions.

  • Proficiency with cloud-based data platformsAWS, Azure, or GCP.


Key Responsibilities

  • Design, build, and maintain event-driven distributed data infrastructure and data applications.

  • Develop and optimize ETL/ELT pipelines to support batch and real-time data workflows.

  • Integrate and normalize diverse data sources, ensuring data quality, accuracy, and consistency.

  • Lead the design and implementation of real-time data processing systems for analytics, operational intelligence, and reporting use cases.

  • Collaborate closely with data scientists, ML engineers, and product teams to build end-to-end data solutions.

  • Define and enforce best practices for data engineering, including:

    • Testing

    • Monitoring

    • Deployment automation

    • Observability

  • Mentor junior engineers and contribute to:

    • Architectural decisions

    • Technical strategy

    • Roadmap planning for the overall data platform.

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