Data Architect

About Company

ReNew is a leading decarbonisation solutions provider and the first Indian clean energy company to list on Nasdaq (Nasdaq: RNW). With 18.5 GW of commissioned and pipeline utility-scale projects, we are a global company with strong Indian roots. Founded in 2011, ReNew is at the forefront of fighting climate change by offering decarbonisation solutions through utility-scale wind and solar offerings, green hydrogen, carbon markets, and energy storage. ReNew has been a pioneer in leveraging digital technologies to accelerate the transition to green energy and address the unique requirements of the B2B segment in India, where we are the market leader. Our mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew is the world’s first clean energy company to be recognised as a Lighthouse by the World Economic Forum. In 2023, we were recognised among ‘Top 15 Climate Tech Companies to Watch’ by the MIT Technology Review. We are a recipient of the Sustainable Market Initiative’s Terra Carta Seal. The COP28 UAE Presidency presented ReNew the ‘Energy Transition Changemaker’ award for developing and deploying the country’s first round-the-clock power project. ReNew’s solar and wind energy projects currently contribute to 1.9% of India’s power capacity and are spread across 150+ sites and 18 Indian states. We have helped prevent 0.5% of India’s total carbon emissions and 1.1% of India’s total power sector emissions, in addition to generating around 130,000 jobs over the past decade.

Job Description

Role- Data Architect

Experienece- 12- 15 years

Location- Gurgoan

Key Responsibilities

• Platform architecture: Define and own the target-state architecture for the Unified Data Platform – Data Mesh principles, medallion lakehouse (Bronze/Silver/Gold), warehouse, and streaming layers on Azure Databricks + Delta Lake – aligned to enterprise architecture and the business roadmap.
• Integration & ingestion: Design scalable ingestion patterns across enterprise systems (SAP, SuccessFactors, payroll, finance) and asset/OT/IoT sources (SCADA, sensor, plant data) – batch, micro-batch, and real-time streaming.
• Governance & catalog: Architect the Unity Catalog governance layer – catalog/schema structure, metadata, lineage, ownership, certification, and discoverability of enterprise data assets.
• Security by design: Embed RBAC/ABAC, masking, encryption in transit and at rest, and auditability to meet DPDPA and SOX-equivalent controls; ensure no production go-live with open vulnerabilities or pending InfoSec / VAPT closure.
• Data modelling standards: Set conceptual/logical/physical and dimensional (star-schema) modelling standards and curated Gold-layer patterns for BI, KPIs, and AI consumption.
• Reusable patterns: Establish reference architectures, blueprints, and reusable platform capabilities to reduce duplication and drive a platform-first, scale-first operating model across business lines.
• AI readiness: Define the architecture for governed AI and “Talk to your Data” conversational access – feature, model-consumption, and access patterns built on trusted data.
• DataOps & operability: Define Dev/UAT/Prod strategy, CI/CD, observability, data quality, and cost/performance optimisation for long-term supportability; provide architectural governance to engineering and SI partners (KPMG, Databricks).
  
  

Experience & Skills

• 12+ years in enterprise data / platform engineering, with 5+ years designing large-scale data platforms as an architect.
• Deep hands-on expertise in Azure Databricks, Delta Lake, Unity Catalog, Spark, and ADLS Gen2; proven medallion / lakehouse architecture experience.
• Strong grounding in data modelling, governance, lineage, and security architecture (RBAC/ABAC, masking, encryption).
• Experience integrating diverse sources including time-series / OT / IoT data; renewable-energy or industrial-domain exposure is an advantage.
• Cloud-native design across Azure (primary) and AWS; strong stakeholder management across business, InfoSec, and enterprise architecture.
• Databricks and Azure Data / Solutions Architect certifications preferred.
  
  

Core Technology Stack

Databricks, Unity Catalog, Delta Lake, Databricks SQL, Spark / Spark SQL, ADLS Gen2, Lakehouse & Medallion Architecture, Dimensional Modelling & Star Schema, Data Warehousing, Streaming (Structured Streaming / Kafka / Event Hubs), Metadata & Master/Reference Data Management, Data Governance, Data Lineage, Data Quality, RBAC/ABAC, Encryption & Masking, CI/CD & DataOps, Power BI, and AWS.

Experience & Skills

• 12+ years in enterprise data / platform engineering, with 5+ years designing large-scale data platforms as an architect.
• Deep hands-on expertise in Azure Databricks, Delta Lake, Unity Catalog, Spark, and ADLS Gen2; proven medallion / lakehouse architecture experience.
• Strong grounding in data modelling, governance, lineage, and security architecture (RBAC/ABAC, masking, encryption).
• Experience integrating diverse sources including time-series / OT / IoT data; renewable-energy or industrial-domain exposure is an advantage.
• Cloud-native design across Azure (primary) and AWS; strong stakeholder management across business, InfoSec, and enterprise architecture.
• Databricks and Azure Data / Solutions Architect certifications preferred.
  
  

Core Technology Stack

Databricks, Unity Catalog, Delta Lake, Databricks SQL, Spark / Spark SQL, ADLS Gen2, Lakehouse & Medallion Architecture, Dimensional Modelling & Star Schema, Data Warehousing, Streaming (Structured Streaming / Kafka / Event Hubs), Metadata & Master/Reference Data Management, Data Governance, Data Lineage, Data Quality, RBAC/ABAC, Encryption & Masking, CI/CD & DataOps, Power BI, and AWS.