Data Engineer

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Department:

Location:

Reporting To:

About the Company:

We are amongst the top 10 largest renewable IPPs in India in terms of total capacity* as of December 31, 2024. We develop, build, operate, and maintain projects through our in-house engineering, procurement, construction, operations & maintenance teams.

Our portfolio of projects includes wind, solar, wind-solar hybrid and firm and dispatchable renewable energy including battery energy storage systems. As of May 31, 2025, our total portfolio stands at approximately 10,069 MWp spread over 48 projects across four states in India.

Job Summary:

As a Data Engineer, you will support the design and implementation of our data architecture, ensuring it is scalable, secure and optimized for renewable energy data. You will collaborate with cross-functional teams to establish a robust data infrastructure that powers advanced analytics, AI, and business intelligence solutions.

Key Responsibilities:

Data Architecture and Strategy:

• Design and oversee the implementation of a scalable, efficient, and secure data architecture that supports real-time and batch processing for renewable energy data analytics.
• Define and implement a long-term data strategy aligned with organizational goals and analytics requirements.
• Lead the selection of appropriate data platforms, tools, and technologies based on current and future needs.

Data Governance and Quality:

• Establish data governance frameworks, including data standards, policies, and best practices to ensure data integrity, security, and compliance with industry regulations.
• Implement processes for monitoring, maintaining, and improving data quality across all data sources.
• Ensure data lineage and cataloging for improved traceability and usability.

Data Integration and Modeling:

• Design and implement data models and schemas that optimize storage and access for renewable energy datasets, such as SCADA data, IoT sensor data, and weather forecasts.
• Lead efforts to integrate data from diverse sources, including third-party APIs, legacy systems, and cloud-based services.
• Develop reusable data patterns and blueprints for scalable and efficient data pipelines.
• Build and maintain ETL/ELT pipelines that process and transform large volumes of structured and unstructured data.

Platform Implementation and Optimization:

• Oversee the setup of cloud-based platforms for big data storage, computation, and analytics.
• Implement and optimize data storage solutions, such as data lakes and data warehouses, for cost and performance.
• Ensure high availability, disaster recovery, and scalability of data systems.

Innovation and Continuous Improvement:

• Stay updated with emerging data technologies and trends and recommend their adoption to enhance the data ecosystem.
• Foster a culture of innovation within the data analytics department, promoting the use of advanced tools and methodologies.
• Mentor and guide the data engineering and analytics team in adopting architectural best practices.

Qualifications and Skills:

Essential:

• Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 2-5 years of experience in data architecture, data engineering, or related roles, with a proven track record of building scalable data solutions.
• Deep expertise in cloud platforms (AWS, Azure, or GCP) and big data technologies (e.g., Apache Spark, Hadoop).
• Proficiency in data modeling, schema design, and database optimization for relational and NoSQL databases.
• Strong understanding of ETL/ELT processes and tools (e.g., Apache Airflow, AWS Glue, Azure Data Factory).
• Experience implementing data governance and quality frameworks.
• Familiarity with renewable energy datasets, such as SCADA, IoT, and meteorological data, is highly desirable.

Desirable:

• Knowledge of renewable energy systems, energy markets, and sustainability practices.
• Experience in designing data platforms for AI/ML applications and predictive analytics.
• Strong leadership and communication skills, with the ability to collaborate across technical and business teams.