Senior Data Engineer

7 days ago


Pune, Maharashtra, India Byond Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Senior Data Engineer

Location:
Pune

Experience:
4–6 years

Education:
Bachelor's or Master's degree in Computer Science, Information Technology, or a related field

Job Description

Byond is hiring for a
confidential client
in the manufacturing domain. We are seeking a highly skilled
Senior Data Engineer
with strong expertise in
Azure Databricks, PySpark, and distributed computing
. The role involves developing and optimizing scalable ETL pipelines to support
manufacturing analytics
. You will be working with
high-frequency industrial data
to enable both
real-time
and
batch data processing
.

Key Responsibilities

  • Build scalable
    real-time and batch data processing workflows
    using Azure Databricks, PySpark, and Apache Spark.
  • Perform
    data pre-processing
    , including cleaning, transformation, deduplication, normalization, encoding, and scaling, to ensure high-quality inputs for downstream analytics.
  • Design, implement, and maintain
    cloud-based data architectures
    , including data lakes, lakehouses, and warehouses, aligned with
    Medallion Architecture
    .
  • Deploy and optimize
    data solutions
    on Azure (preferred), AWS, or GCP, focusing on
    performance, security, and scalability
    .
  • Develop and optimize
    ETL/ELT pipelines
    for structured and unstructured data sourced from
    IoT, MES, SCADA, LIMS, and ERP systems
    .
  • Automate workflows using
    CI/CD pipelines
    and DevOps best practices while ensuring
    security and compliance
    with industry standards.
  • Monitor, troubleshoot, and continuously improve
    data pipelines
    for high availability and reliability.
  • Utilize
    Docker and Kubernetes
    for containerized and scalable data processing.
  • Collaborate closely with
    automation teams, data scientists, and engineers
    to provide clean, structured data for
    AI/ML models
    .

Required Skills & Experience

  • 4+ years
    of proven experience in data engineering, with a strong focus on cloud platforms such as
    Azure (preferred), AWS, or GCP
    .
  • Proficiency in
    PySpark, Azure Databricks, Python, and Apache Spark
    .
  • Expertise in multiple database technologies, including:
  • Relational databases (e.g.,
    SQL Server, PostgreSQL
    )
  • Time-series databases (e.g.,
    InfluxDB
    )
  • NoSQL databases (e.g.,
    MongoDB, Cassandra
    )
  • Hands-on experience with
    containerization tools
    such as Docker and Kubernetes.
  • Strong
    analytical, problem-solving, and debugging skills
    , with meticulous attention to detail.
  • Excellent
    communication and collaboration skills
    with a proven track record of effective teamwork.
  • Comfortable working in a
    dynamic, fast-paced startup environment
    , with the ability to adapt quickly to changing priorities and responsibilities.

Nice-to-Have Skills

  • Familiarity with
    MLOps and DevOps practices
    , including
    model lifecycle management
    .
  • Experience working with
    industrial data sources
    like IoT, MES, SCADA, LIMS, and ERP.

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