Data Engineer

About Company

Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India.

Job Description

Job Title: Data Engineer
Location: Gurugram Haryana
Experience: 2–4 Years
Employment Type: Full-Time

Job Overview
We are seeking a Data Engineer with 2–4 years of hands-on experience to join our ReD team in Gurugram. The ideal candidate will have strong experience building and maintaining scalable data pipelines, working with cloud-based big data platforms, and collaborating with data architects, data scientists, and business stakeholders to deliver high-impact analytical solutions.
This role involves working on enterprise-scale data platforms, diagnosing and improving existing architectures, and ensuring reliable, secure, and high-performance data systems.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using industry best practices
Collaborate with data architects to design and enhance data architecture, ensuring performance, scalability, and security
Analyze existing data systems to identify gaps, inefficiencies, and improvement opportunities
Build and manage data lakes and data warehouses for analytical and reporting use cases
Optimize data ingestion, transformation, and delivery workflows for performance and reliability
Develop, test, and maintain modular, reusable, and efficient code for data processing
Work closely with data scientists and analysts to enable data pipelines for ML models and advanced analytics
Ensure data quality, consistency, and availability across platforms
Participate in Agile development processes, including sprint planning, reviews, and retrospectives
Communicate effectively with business stakeholders and leadership to understand data needs and translate them into technical solutions

Technical Skills & Requirements

2–4 years of experience in data engineering or related roles
Strong proficiency in Python for data engineering and automation
Solid hands-on experience with distributed data processing frameworks, including:

Apache Spark
Spark SQL
Spark Streaming (preferred)
Kafka or similar streaming platforms
Hive or equivalent data warehousing technologies

Experience working with Microsoft Azure
Strong understanding of data lake and data warehouse architectures
Proficiency in SQL and data modeling concepts
Hands-on experience with Git and collaborative development workflows