You will be taken to LTIMindtree’s own careers page to apply. Job ID 1492199.
Job description
Experience
12 Years
Role Overview
We are seeking an experienced Databricks Data Architect to lead the design architecture and implementation of enterprisescale data platforms on Databricks The ideal candidate should possess strong expertise in modern data engineering practices dimensional data modeling and Databricks Lakehouse architecture
The candidate will act as the technical owner of the data platform providing architectural guidance establishing best practices mentoring development teams and ensuring successful delivery of scalable highperformance data solutions
Key Responsibilities
Architecture Solution Design
Design and implement enterprisescale data platforms using the Databricks Lakehouse architecture
Define endtoend data architecture including ingestion transformation storage governance and consumption layers
Establish architectural standards framework guidelines coding best practices and reusable design patterns
Lead technical decisions related to scalability performance optimization reliability and security
Conduct architecture reviews and provide recommendations to project teams
Data Engineering Databricks Implementation
Design and build scalable ETLELT pipelines using PySpark on Databricks
Architect and implement Bronze Silver Gold data transformation frameworks
Design and manage Delta Lake based storage architecture including partitioning optimization and data lifecycle management
Implement Databricks Lakeflow pipelines for data orchestration and automation
Define data quality validation reconciliation and monitoring frameworks
Oversee CICD and DevOps practices for data engineering projects
Data Modeling Analytics Enablement
Design and implement enterprise data models using Dimensional Modeling techniques
Develop Star Schemas Fact Tables Dimension Tables and conformed dimensions
Define business metrics KPI layers and semantic models
Architect and implement Metric Views and curated Gold datasets for reporting and analytics
Work closely with business stakeholders to translate requirements into scalable analytical models
Technical Leadership
Provide technical leadership and mentorship to data engineers and developers
Perform code reviews and ensure adherence to architecture standards
Troubleshoot complex technical issues and guide teams in solution design
Support estimation solution proposals and technical governance activities
Drive adoption of modern data engineering and cloudnative best practices
Required Technical Skills
Core Databricks Skills
Databricks Lakehouse Architecture
Databricks Workflows Lakeflow
Delta Lake
Unity Catalog
Databricks SQL
Performance Tuning Optimization
Data Engineering
PySpark
Spark SQL
ETL ELT Design
Data Pipeline Development
Data Quality Frameworks
Batch and Incremental Processing
Data Modeling
Dimensional Data Modeling
Star Schema Design
Fact Dimension Modeling
Slowly Changing Dimensions SCD
Metric View Design
Analytical Data Modeling
Cloud Integration
Azure Databricks preferred
ADLS Gen2
Azure Data Factory ADF
Eventbased and Batch Ingestion Patterns
Data Governance and Security
Programming
Python
SQL
Git
CICD Frameworks
Desired Skills
Data Warehouse Modernization experience
Experience migrating legacy EDW solutions to Databricks
Exposure to Data Mesh and Medallion Architecture
Knowledge of Data Governance Metadata Management and Data Cataloging
Experience supporting BI platforms such as Power BI Tableau or Looker
Leadership Expectations
The candidate should be capable of
Owning the complete Databricks implementation lifecycle
Defining targetstate architecture and roadmap
Reviewing designs and code produced by team members
Guiding developers on PySpark optimization and data modeling best practices
Driving technical discussions with client architects and business stakeholders
Ensuring scalability maintainability and longterm sustainability of the platform
Providing architectural governance across multiple workstreams
