Applied AI Engineer-DATA - Lead Software Engineer I
Deloitte (company site, opens in a new tab)8+ yrsBengaluruOn-siteDirect career pageEst. 28–45 LPA
Posted 20h ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Deloitte
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Deloitte you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own and manage end-to-end data load lifecycles across warehouse and lakehouse platforms, ensuring data quality, scheduling, and production support.
- Architect and implement dimensional and lakehouse data models including governance and access controls like Unity Catalog.
- Lead delivery of GenAI solutions on enterprise data, manage project lifecycle from mobilisation to operations, and lead a multidisciplinary team while tracking SLAs, costs, and business value.
Minimum Requirements
- Bachelor's or Master's degree in Computer Science, IT, Engineering, Data Science, or related field.
- Minimum 8 years of technology experience, including significant enterprise data program delivery and leadership experience.
- Hands-on expertise with Databricks (Spark/PySpark, Delta Lake, Workflows, Unity Catalog) and Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Notebooks).
- Proven experience with end-to-end cloud data pipelines, strong SQL and Python skills, and working knowledge of CI/CD and cloud platforms (Azure, AWS, or Google Cloud).
Ideal Candidate Profile
- Experienced in leading and mentoring multidisciplinary teams including data engineers, BI developers, and GenAI engineers in an enterprise environment.
- Strong background in dimensional modelling, data warehousing fundamentals, and delivering GenAI solutions such as RAG, vector search, or LLM applications.
- Comfortable managing full project delivery lifecycle, including stakeholder management, budgeting, risk management, and ensuring operational excellence.