We are seeking an experienced Data Architect Lead to design, develop, and maintain scalable data solutions on Azure and Databricks as part of our enterprise data modernization initiatives.

The ideal candidate will have a strong background in data pipeline development, data integration frameworks, and cloud-based data engineering, with deep expertise in tools such as Databricks, Azure Data Factory, Alteryx, Ab Initio, Talend, and Informatica.

This role will lead the design and delivery of high-performance, governed data architectures for large-scale enterprise clients, ensuring data reliability, compliance, and analytics readiness.

Key Responsibilities :

- Design and implement scalable, reusable data pipelines using Databricks (PySpark, Delta Lake) and Azure Data Factory, ensuring high throughput and low latency.

- Develop and maintain Common Data Platforms (CDP) and Medallion Architecture-based data lakes to consolidate legacy systems and improve enterprise data availability.

- Create and manage backend data services using Python, Spark, or C#, ensuring high performance, reliability, and scalability.

- Develop metadata-driven data ingestion frameworks capable of handling schema drift and supporting multi-source data integration.

- Lead data integration and migration initiatives using Talend, Ab Initio, Alteryx, and Informatica, transforming traditional ETL workflows into modern cloud-native pipelines.

- Implement data quality, lineage, and governance frameworks, including Unity Catalog, Data Stewardship, Data Catalog, and Master Data Management (MDM).

- Design and maintain GDPR/CCPA-compliant data processing pipelines aligned with global data privacy standards.

- Build and optimize Feature Store Data Marts to support AI/ML analytics teams and downstream BI consumers.

- Collaborate with Data Scientists, BI Developers, Product Owners, and business stakeholders to deliver data-driven insights and business outcomes.

- Mentor junior engineers and promote best practices in data engineering, CI/CD pipelines, and infrastructure-as-code.

- Implement Redis and caching strategies to optimize performance and reduce latency in analytics workloads.

- Take end-to-end ownership of assigned modules, ensuring timely delivery, documentation, and performance optimization.

Technical Environment :

Cloud Platforms :

- Microsoft Azure (Data Factory, Synapse, Data Lake, Databricks)

- AWS (S3, EC2, Glue, Redshift)

Data Engineering Tools :

- Databricks (DLT, Auto Loader, Unity Catalog)

- Talend

- Ab Initio

- Informatica

- Alteryx

Programming Languages :

- Python

- PySpark

- SQL

- Unix Shell Scripting

- Data Modeling

- Dimensional Modeling

- Relational Modeling

- Medallion Architecture

- DevOps / CI-CD

- GitHub Actions

- Azure DevOps

- Databricks Asset Bundles (DABs)

Data Governance & Security :

- RBAC / ABAC

- Data Stewardship

- Master Data Management (MDM)

- GDPR / CCPA Compliance

Monitoring & Scheduling :

- Apache Airflow

- Azure Logic Apps

- Azure Monitor

Required Qualifications :

- 12+ years of experience in Data Engineering, Data Architecture, or ETL Development.

- Proven experience leading Azure + Databricks data modernization or migration programs.

- Strong experience with data integration platforms such as Talend, Informatica, Ab Initio, and Alteryx.-

Hands-on expertise in PySpark, SQL, and Azure Data Services.

- Deep understanding of data modeling, data quality, and governance frameworks.

- Experience implementing real-time and batch data ingestion pipelines using technologies such as Kafka, Kinesis, or Event Hub.

- Excellent problem-solving, communication, and stakeholder management skills.

Preferred Qualifications :

- Bachelor's degree in Computer Science, Engineering, or a related field.

- Azure Data Engineer Certification or equivalent cloud certifications.

- Experience supporting AI/ML data preparation pipelines and Feature Store design.

- Familiarity with Databricks cost optimization strategies and cluster governance.

- Strong analytical thinking and problem-solving capabilities.

Why Join Us :

- Be part of a large-scale data modernization journey with a global enterprise brand.

- Work with cutting-edge cloud and data engineering technologies.

- Collaborate with a highly skilled team of architects, analysts, and data scientists.

- Opportunity to lead innovation in enterprise-scale data transformation initiatives