Collaborate with stakeholders and source data system teams to understand data requirements
Architect and implement scalable workspace, data lake, dimensional models, data pipelines, data warehouses and other ETL/ELT processes using Fabric.
Work with Fabric assets, Power BI, and other services to build end-to-end data solutions
Ensure data quality, security, and compliance with regulations by implementing data validation, logging, monitoring, and role-based access controls.
Perform root cause analysis on internal/external data and processes to answer specific business questions and identify opportunities for improvement.
Manage platform cost optimization, data quality/governance, and performance tuning
Follow software quality process and methodology standards, including those for design, data quality, code, version control, defect/change request tracking, documentation, work product review, unit testing and environment management.
Review requirements / user stories and provide feedback to the team. Includes participation/input to the requirements process
Integrate AI/ML models and GenAI capabilities into data products and workflows
Help the QA and functional team to identify and define testing strategies for existing and new features
Ability to ensure that solutions developed by development teams fit the business needs
Able to work under pressure and meet deadlines
Comfortable working in evening hours (2pm to 11pm IST)

8+ years of experience in data engineering roles, preferably in a global enterprise environment
Strong hands-on experience with Microsoft Fabric, Data Lake, Data Warehouse, Data pipelines and related broader Microsoft ecosystem.
Expertise in Power BI semantic models and datasets for building dashboards and reports
Strong DAX and Power Query skills
Expert proficiency in SQL, Python, PySpark for data processing
Must have implemented ETL solutions to integrate data from various sources into Azure Data Lake and Data Warehouse
Good knowledge of EDW
Strong understanding of data management processes, such as data normalisation and modelling, as well as data security principles, data access control and confidentiality.
Good to have experience in Copilot or any AI/ML solutions with at least basic exposure to GenAI (LLMs, prompt engineering, AI API integration)
Familiar with software quality assurance best practices & methodologies, and tools like Jira, GIT, etc.
Experience with other SaaS/Cloud ERP, CRM systems like NetSuite or Salesforce or SAP S4/Hana is a plus
Excellent problem-solving, communication, and collaboration skill

Lead Data Engineer

Key skills