Pyspark Developer (10- 15 Years), Pan India

Full–time

Posted on: 12 hours ago

Dear Professionals,

Greetings from Tata Consultancy Services (TCS)!!!

Job Title : Pyspark Developer

Experience : 10-15 Years

Location: Pan India

Mode of Interview : Virtual

Mode of work : Work from Office

Key Responsibilities
  • Data Pipeline Development: Design and implement robust ETL (Extract, Transform, Load) pipelines to handle massive datasets using PySpark and DataFrames.
  • Performance Optimization: Fine-tune PySpark applications, tune SQL queries, and troubleshoot performance issues in distributed computing environments.
  • Data Processing:
  • Process and analyze data from various sources (SQL/NoSQL) and perform data enrichment.
  • Collaboration: Work with data engineers, data scientists, and stakeholders to understand data requirements.
  • Documentation: Create technical documentation, including HLD (High-Level Design) and LLD (Low-Level Design).

  • Required Skills and Qualifications
  • Core Technical Skills: Expertise in Python, PySpark (Spark SQL/DataFrames), and SQL.
  • Big Data Ecosystem: Strong understanding of Hadoop, Spark architecture, and distributed computing principles.
  • Data Handling: Experience with large-scale data manipulation (CDC - Change Data Capture).
  • Experience: Generally requires 3–6+ years of experience in data engineering or software development.
  • Tools: Familiarity with Cloud Platforms (AWS, Azure) and Kafka is frequently required.

If you are Interested in the above opportunity kindly share your updated resume to pullagura.gokulsaiakhil@tcs.com immediately with the details below (Mandatory)

Name:

Contact No.

Email id:

Skillset:

Total exp:

Relevant Exp:

Fulltime highest qualification (Year of completion with percentage scored):

Current organization details (Payroll company):

Current CTC:

Expected CTC:

Notice period:

Current location:

Preffered Location

Any gaps between your education or career (If yes pls specify the duration):

Will you be able to join within 30/45 days? (Yes/NO)