Databricks Data Architect.

Location: Mumbai Onsite.

Salary: Negotiable.

Immediate Joiners.

Local Mumbai Only!.

We are seeking an experienced Databricks Data Architect with a strong background in designing scalable data platforms in the manufacturing or energy sector.

The ideal candidate will have over 10 years of experience in designing and implementing enterprise-grade data solutions, with strong proficiency in Azure Databricks and big data technologies.

Required Skills and Experience :

- Strong proficiency in Azure Databricks and big data technologies (Apache Spark, Kafka, Event Hub).

- Deep understanding of data modeling, data lakes, batch and real-time/streaming data processing.

- Proven experience with high volume data pipeline orchestration and ETL/ELT workflows.

- Experience designing and implementing data lakes, data warehouses, and lakehouse architectures.

- Proven experience in designing and implementing data visualization solutions for actionable insights.

- Strong understanding of data integration patterns, APIs, and message streaming (e., Event Hub, Kafka).

- Experience with metadata management, and data quality frameworks.

- Excellent problem-solving skills and the ability to translate business needs into technical solutions.

- Experience with structured and unstructured data ingestion, transformation, and processing at scale.

- Excellent communication, documentation, and stakeholder management skills.

Key Responsibilities :

- Architect and deliver scalable, cloud-native data solutions to support both real-time and batch processing needs.

- Work closely with business and technical stakeholders to understand business requirements, define data strategy, governance, and architecture standards.

- Ensure data quality, integrity, and security across platforms and systems.

- Define data models, data integration patterns, and governance frameworks to support analytics use cases.

- Collaborate with DevOps and Engineering teams to ensure robust CI/CD pipelines and deliver production-grade deployments.

- Define and enforce data architecture standards, frameworks, and best practices across data engineering and analytics teams.

- Implement data governance, security, and compliance measures, including data cataloguing, access controls, and regulatory adherence.

- Lead capacity planning and performance tuning efforts to optimize data processing and query performance.

- Create and maintain architecture documentation, including data flow diagrams, data models, entity-relationship diagrams, system interfaces etc.

- Design clear and impactful visualizations to support key analytical objectives.