Overview

Starting Date: December 2026/ January 2027

Responsibilities

• Build and operate ingestion and ETL/ELT pipelines across field tools, supply chain systems, middleware APIs, legacy systems and partner platforms, so that priority data is delivered reliably, incrementally and observably.
• Design and own the target-state lakehouse architecture, enterprise data warehouse, data marts and data models, ensuring a scalable, secure and maintainable platform that separates transactional and analytical workloads and meets data residency, privacy and retention requirements.
• Lead the phased extraction and migration of high-volume historical data from legacy systems, reconciling large and complex datasets without disrupting live operations.
• Establish and operate platform environments, infrastructure as code, CI/CD, identity, access controls, encryption and audit logging together with IT and Security, keeping the platform secure, repeatable and cost-efficient.
• Implement the data catalogue, data dictionary, metadata management, automated lineage and data-quality monitoring, translating governance policies into measurable and enforceable platform controls.
• Build trusted, reusable data products for reporting, traceability, compliance, impact measurement, member services and AI/ML use cases, enabling Power BI and analytics teams to work from governed data.

Qualifications

• A degree in Computer Science, Engineering or a related field, or equivalent practical experience.
• Strong hands-on experience in data engineering, architecture and production data-platform delivery, including responsibility for ingestion and ETL/ELT pipelines, medallion (bronze/silver/gold) lakehouse, data warehouse and data mart design, distributed processing at scale, and the migration and reconciliation of large or complex datasets, with a track record of delivering platforms that operate in production.
• Professional certifications in Databricks, cloud platforms (AWS or Azure or GCP) or data architecture are desirable but not required.
• Applies expert SQL and strong Python to model, transform and reconcile large datasets efficiently.
• Builds and operates production lakehouse workloads and pipelines using Spark/PySpark, Delta Lake, Unity Catalog and Databricks Workflows, applying medallion architecture.
• Fluency in written and spoken English is essential.
• Knowledge of data governance, security and data quality practices, including access controls, lineage, cataloguing and monitoring frameworks.
• Proficiency in Hindi, Gujarati, Marathi, Tamil or other Indian languages is desirable to support collaboration with local teams, partners and field-level stakeholders.

Benefits

• Hybrid working opportunity, with the office based in Delhi.
• The opportunity to work from anywhere in the world for up to one month per year
• Flexible working, with core hours from 10 am to 4 pm local time
• Continuous learning and development
• Pension scheme
• A generous annual leave package, including paid holiday, public holidays, additional paid days off during the festive season, study and exam days, and extra discretionary leave for life events such as family weddings or moving home
• Enhanced parental benefits
• The opportunity to make your mark and make a difference.
• Trustworthy (including honest, transparent, credible)
• As having Integrity (including responsible, authentic)
• Positive (including problem-solving, pragmatic)
• Engaging (including adaptable, inclusive, holistic)
• Daring (including courageous, innovative, game-changing)