Applied AI Engineer-DATA - Lead Software Engineer I

Deloitte Development LLC; Bengaluru; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Deloitte Development LLC is seeking a Lead Applied AI Platform Engineer in Bengaluru to own and optimize data load lifecycles across warehouse and lakehouse environments. You will architect data models with governance, build batch and streaming pipelines on Fabric and Databricks, and deliver GenAI solutions on enterprise data.

You will lead a multidisciplinary team, oversee delivery from mobilisation to operations, and ensure SLAs, data quality, and cost efficiency while collaborating with

Qualifications

• Bachelor's or master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 8+ years of technology experience with enterprise data programmes and leading delivery/technical teams.
• Hands-on depth in Databricks (Spark/PySpark, Delta Lake, Workflows) and Unity Catalog.
• Hands-on depth in Microsoft Fabric (Lakehouse, Data Factory, Notebooks, Power BI).
• Proven experience owning end-to-end data load pipelines in a cloud environment.
• Strong dimensional modelling and data warehousing fundamentals.
• Experience delivering GenAI solutions on enterprise data (RAG, vector search, LLM apps).
• Advanced SQL and Python; working knowledge of CI/CD and cloud platforms (Azure, AWS, GCP).
• Strong communication, stakeholder management, and decision-making skills.

Responsibilities

• Own end-to-end data load lifecycles across warehouse and lakehouse platforms.
• Architect dimensional and lakehouse data models with governance and access controls.
• Design and build batch and streaming pipelines using Fabric and Databricks.
• Design and deliver GenAI solutions on enterprise data.
• Own delivery from mobilisation through UAT, go-live, hypercare, and transition to operations.
• Track SLAs, data quality, cost, and business value; escalate if delivery drifts.
• Lead, mentor, and grow a multidisciplinary team; contribute to hiring and capability building.

Skills

Databricks

Microsoft Fabric

GenAI

SQL

Python

Cloud platforms

Data modelling

Leadership

CI/CD

Data workflow orchestration

Education

Bachelor's or Master's in CS/IT/Engineering/Data Science

Tools

Unity Catalog

Delta Lake

Job description

Lead Applied AI Platform engineer

Key Responsibilities

• Own end-to-end data load lifecycles across warehouse and lakehouse platforms, including ingestion, transformation, data quality validation, reconciliation, scheduling, and production support.
• Architect dimensional and lakehouse data models, along with the governance and access controls that go with them, including Unity Catalog.
• Design and build batch and streaming pipelines using Microsoft Fabric (Data Factory, Dataflows Gen2, notebooks, Lakehouse, Warehouse) and Databricks (Spark, Delta Lake, Workflows), selecting the right platform for each client context.
• Design and deliver GenAI solutions on enterprise data, such as RAG applications, vector search, and embedding pipelines, including the guardrails and evaluation approach.
• Own delivery from mobilisation through UAT, go-live, hypercare, and transition to operations, managing scope, budget, risks, and stakeholders.
• Track pipeline SLAs, data quality, cost consumption, and business value, and **escalate early when delivery drifts**.
• Lead, mentor, and grow a multidisciplinary team of data engineers, BI developers, and GenAI engineers, and contribute to hiring and capability building.

Required Skills and Attributes

• Bachelor's or master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 8+ years of technology experience, including significant experience delivering enterprise data programme's and leading delivery or technical teams.
• Hands-on depth in Databricks, including Spark or PySpark, Delta Lake, Databricks Workflows, and Unity Catalog.
• Hands-on depth in Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Factory pipelines, Notebooks, and Power BI integration.
• Proven experience owning end-to-end data load pipelines in a cloud environment.
• Strong dimensional modelling and data warehousing fundamentals, including star schemas, slowly changing dimensions, and performance optimisation.
• Practical experience delivering GenAI solutions on enterprise data, such as RAG, vector search, or LLM-based applications.
• Advanced SQL and strong Python skills, with working knowledge of CI/CD and cloud platforms (Azure, AWS, or Google Cloud).
• Strong communication, stakeholder management, and decision-making skills.

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