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

Roles and responsibilities:

Build optimized and scalable data pipelines using Python, SQL, and distributed processing frameworks such as Spark.
Maintain robust ETL/ELT workflows to integrate structured and semi-structured data from multiple internal and external systems.
Ensure data quality, lineage, validation, and monitoring across all ingestion and transformation layers.
Build reusable datasets, analytics marts, and query-optimized schemas to support diverse use cases including reporting, forecasting, personalization, and operational automation.
Translate raw data into accessible, well-governed, analysis-ready formats.
Follow coding standards, documentation requirements, and review mechanisms to ensure high engineering rigor
Provide data-driven insights and recommendations to support operational efficiency and strategic decision-making.
Collaborate with analytics teams to identify trends, anomalies, or optimization opportunities across operational and customer-facing data.
Strong programming skills in Python, SQL, and experience with Pandas, NumPy, Spark or similar distributed systems.
Proven track record of building end-to-end data pipelines and delivering production-grade data solutions.
Experience using data to derive insights, optimize systems, and improve business outcomes.
Ability to work in fast-paced environments and manage multiple priorities simultaneously
Excellent communication, stakeholder management, and documentation abilities
Strong understanding in distributed computing frameworks, particularly Spark, Spark-SQL, Kafka, Spark Streaming, Hive, Azure Databricks etc
Knowledge in using cloud platforms preferably Azure.
Knowledge of Azure data factory, logic app, Analysis service, Azure blob storage etc.
Ability to work in a team in an agile setting, familiarity with JIRA and clear understanding of how Git works

 

Experience - 1-3 Years

Location - Gurugram, Haryana