Job Title:
Data Engineer / Data Warehouse Developer
Location:
Mumbai
Reports to:
Head of Engineering
Direct Reports:
N/A
Primary Purpose
To design, build, and maintain a scalable internal data repository that consolidates data from key business systems (operational platforms, finance, sales & marketing, and timesheets) into a secure, well-modelled cloud data warehouse to power analytics and self‑service reporting in Power BI
Main Responsibilities:
Technology
- Design, develop, and maintain robust data pipelines to ingest data from multiple internal systems via APIs, integration platforms, and batch processes into a central Snowflake data warehouse.
- Model and implement scalable data warehouse structures (staging, core, marts) to support analytics and reporting use cases across finance, sales & marketing, operations, and resourcing/timesheets
- Collaborate with business stakeholders (Finance, Sales, Marketing, Operations, HR/Resourcing) to understand data requirements, map source systems, and define a consistent, joined‑up data model.
- Implement and maintain ELT/ETL processes using appropriate tools (e.g. integration platforms, orchestration tools, SQL, scripting) ensuring performance, reliability, and maintainability
- Work closely with BI developers and analysts to expose clean, well‑documented datasets and semantic models optimised for Power BI
- Ensure data quality and integrity through validation rules, reconciliation checks, and monitoring across the full data pipeline from source to reporting.
- Optimise compute, storage, and queries for cost‑efficiency and performance, including clustering, caching, and workload management
- Maintain clear technical documentation for data models, data flows, lineage, and transformations to support collaboration and ongoing maintenance.
- Stay current with modern data engineering practices, tooling, and cloud data platform capabilities, proposing improvements to the data architecture and pipelines
Process, Quality and Information Security
- Manage your own workload, delivering committed work within the iteration and to agreed definitions of done.
- Ensure all data pipelines and transformations are appropriately tested (unit, integration, regression) and integrated into the release process, supporting higher levels of deployment automation
- Contribute to and adopt CI/CD practices for data and analytics assets (e.g. version control for SQL/scripts, automated deployment of data models and pipelines).
- Adhere to Information Security policies and implement "security by design" across data pipelines and platforms, including access control, encryption, and secure handling of PII/financial data.
- Collaborate with IT Operations, Information Security, and Software Engineering teams to align on infrastructure requirements, environments, and operational support models
- Support change and release processes (including CAB where required), ensuring changes to data pipelines and warehouse structures are well‑planned and low risk
Professional skills/ experience:
- Strong experience as a Data Engineer / Data Warehouse Developer or similar role, ideally in a cloud‑native environment
- Expert SQL skills with experience building and optimising complex queries and transformations
- Hands‑on experience designing and implementing data warehouses or data lakehouses (star/snowflake schemas, dimensional modelling, slowly changing dimensions, etc.)
- Practical experience with cloud data warehouses, databases, roles, virtual warehouses, performance tuning, cost optimisation
- Experience ingesting data from APIs and/or integration platforms (e.g. iPaaS tools, ETL/ELT orchestrators) and working with a variety of data formats (JSON, CSV, parquet, etc.)
- Familiarity with BI / visualisation tools, preferably Power BI, and how to structure data for efficient reporting and self‑service analytics
- Understanding of data quality management, metadata, data lineage and data governance practices
- Experience with cloud platforms (e.g. Azure, AWS, or GCP) and modern DevOps practices (version control, CI/CD, environment management)
- Scripting or programming experience (e.g. Python) for data processing and automation is highly desirable
- Knowledge of information security standards and regulatory requirements relating to data (e.g. ISO27001, GDPR) is a plus
Personal Qualities
- Strong problem solver who enjoys working with complex, messy data and turning it into reliable, usable assets
- Able to build trust and rapport across Finance, Sales, Marketing, Operations, IT and Engineering teams
- Clear and confident communicator, capable of explaining technical concepts to non‑technical stakeholders
- Team player with a collaborative, flexible approach and a "can do" mindset
- Able to prioritise effectively, manage multiple data initiatives, and resolve issues quickly
- High attention to detail with a focus on data accuracy, consistency, and reliability
