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

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

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.