Python/Pyspark, Bigquery with GCP, Apache Iceberg

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:

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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.