Python/Pyspark, Bigquery with GCP, Apache Iceberg

9 hours ago

Hyderabad, Telangana, India Tata Consultancy Services Full time ₹ 4,00,000 - ₹ 6,00,000 per year

TCS Hiring Virtual Drive ***
12-Nov-25 Python/Pyspark, Bigquery with GCP, Apache Iceberg

TCS - Hyderabad

12 PM to 1 PM

Immediate Joiners

5 to 7 years

Role**
Python/Pyspark, Bigquery with GCP, Apache Iceberg

Exp -
5 to 7 years

Please read Job description before Applying

NOTE: If the skills/profile matches and interested, please reply to this email by attaching your latest updated CV and with below few details:

Name:

Contact Number:

Email ID:

Highest Qualification in: (Eg. B.Tech/B.E./M.Tech/MCA/M.Sc./MS/BCA/B.Sc./Etc.)

Current Organization Name:

Total IT Experience-
5 to 7 years

Location : Hyderabad

Current CTC

Expected CTC

Notice period: Immediate

Whether worked with TCS - Y/N

Must-Have**

(Ideally should not be more than 3-5)

  • Strong proficiency in
    Python
    programming.
  • Hands-on experience with
    PySpark
    and
    Apache Spark
    .
  • Knowledge of
    Big Data
    technologies (Hadoop, Hive, Kafka, etc.).
  • Experience with
    SQL
    and relational/non-relational databases.
  • Familiarity with
    distributed computing
    and
    parallel processing
    .
  • Understanding of
    data engineering
    best practices.
  • Experience with
    REST APIs
    ,
    JSON/XML
    , and data serialization.
  • Exposure to
    cloud computing
    environments.

Good-to-Have

  • 5+ years of experience in Python and PySpark development.
  • Experience with
    data warehousing
    and
    data lakes
    .
  • Knowledge of
    machine learning
    libraries (e.g., MLlib) is a plus.
  • Strong problem-solving and debugging skills.
  • Excellent communication and collaboration abilities.

SN

Responsibility of / Expectations from the Role

1

  • Develop and maintain scalable data pipelines using
    Python
    and
    PySpark
    .
  • Design and implement
    ETL (Extract, Transform, Load)
    processes.
  • Optimize and troubleshoot existing PySpark applications for performance.
  • Collaborate with cross-functional teams to understand data requirements.
  • Write clean, efficient, and well-documented code.
  • Conduct code reviews and participate in design discussions.
  • Ensure data integrity and quality across the data lifecycle.
  • Integrate with cloud platforms like
    AWS
    ,
    Azure
    , or
    GCP
    .
  • Implement data storage solutions and manage large-scale datasets.

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