Python_PySpark Developer on GCP

V2 Solutions; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

V2 Solutions, Hyderabad-based, seeks a data engineer with 4 to 8+ years of Python and PySpark experience to build robust data pipelines. You will design ETL processes, optimize Spark jobs, and collaborate with cross-functional teams to meet data requirements.

Proficiency in SQL and experience with Hadoop, Hive, Kafka, and cloud platforms is valued. This role emphasizes code quality, data integrity, and scalable solutions across on-prem and cloud environments, with opportunities to work on

Qualifications

• 4 to 8+ years of experience with Python and PySpark.
• Strong proficiency in Python programming.
• Hands-on experience with PySpark and Apache Spark.
• Knowledge of Hadoop, Hive, Kafka and other Big Data technologies.
• 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.

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

Skills

Python

PySpark

Spark

Big Data

SQL

REST APIs

Cloud

Tools

Hadoop

Hive

Kafka

Job description

Role & responsibilities

Job Requirements*

• 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 cloud computing environments.

Key Responsibilities*

• 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.