Python Software Developer

Tata Consultancy Services; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Tata Consultancy Services (TCS) invites applications for a data engineering role focusing on Python and PySpark. The candidate will develop scalable data pipelines, design ETL processes, and optimize PySpark workloads while collaborating with cross-functional teams.

Required are 4–8+ years of Python/PySpark experience, strong SQL skills, and familiarity with Big Data technologies (Hadoop, Hive, Kafka) along with cloud exposure (GCP/AWS/Azure).

Qualifications

• 4–8+ years of Python and PySpark experience.
• Strong proficiency in Python programming.
• Experience with PySpark, Apache Spark.
• Knowledge of Big Data technologies (Hadoop, Hive, Kafka).
• Experience with SQL and databases.

Responsibilities

• Develop and maintain scalable data pipelines using Python and PySpark.
• Design and implement ETL (Extract, Transform, Load) processes.
• Optimize and troubleshoot 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 GCP, AWS or Azure.
• Implement data storage solutions and manage large-scale datasets.

Skills

Python

PySpark

SQL

REST APIs

JSON/XML

Data Modeling

Tools

Apache Spark

Hadoop

Hive

Kafka

GCP

AWS

Azure

Job description

TCS Hiring!!!

Role & responsibilities

• 4 to 8 + Years of experience using Python and Pyspark.
• 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 GCP services and cloud computing environments.

• 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 GCP, AWS or Azure.
• Implement data storage solutions and manage large‑scale datasets.