The ideal candidate will be responsible for designing, implementing, and governing scalable data platforms that support analytics, reporting, AI/ML, and business intelligence initiatives. This role requires deep technical expertise in Databricks, data modeling, cloud data engineering, and architecture best practices.

Qualifications

Experience: 10 to 14 Years

Work location: Hyderabad

Required Skills

- Strong experience in Databricks Lakehouse Platform.
- Expertise in Apache Spark (Pyspark/Scala Spark).
- Hands-on experience with Delta Lake, Unity Catalog, Delta Live Tables, and Databricks Workflows.
- Strong understanding of data warehousing and dimensional modeling concepts.
- Experience with cloud platforms: Microsoft Azure (preferred), AWS, GCP.
- Knowledge of Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Kafka/Event Hubs.
- Expertise in SQL and performance tuning.
- Experience designing ETL/ELT frameworks and data integration solutions.
- Understanding of data governance, security, access controls, and compliance frameworks.
- Experience with DevOps, CI/CD, Infrastructure as Code (Terraform preferred).
- Exposure to BI tools such as Power BI, Tableau, or Looker.

Preferred Skills

- Enterprise Data Architecture.
- Lakehouse Architecture.
- Data Mesh / Data Fabric concepts.
- Master Data Management (MDM).
- Metadata Management.
- Data Governance.
- Real-time Analytics Architecture.
- AI/ML Data Platform Design.




- Experience with Generative AI and LLM-based data solutions.
- Knowledge of Microsoft Fabric.
- Experience with Snowflake, Big Query, or Redshift.
- Exposure to MLOps frameworks and AI governance.
- Experience in regulated industries such as Banking, Healthcare, Insurance, or Retail.

Responsibilities

- Define and implement enterprise-wide data architecture strategies aligned with business objectives.
- Design scalable and secure data platforms using the Databricks Lakehouse architecture.
- Architect batch and real-time data ingestion frameworks from multiple source systems.
- Develop data models, data warehouses, data lakes, and Lakehouse solutions.
- Lead the migration of legacy data platforms to cloud-based contemporary data architectures.
- Define data governance, metadata management, data quality, lineage, and security standards.
- Collaborate with business stakeholders, data engineers, analysts, and data scientists to understand requirements and translate them into technical solutions.
- Establish architecture frameworks, best practices, and reusable design patterns.
- Optimize data pipelines and platform performance for scalability and cost efficiency.
- Support advanced analytics, AI/ML, and GenAI use cases through robust data architecture.
- Conduct architecture reviews and provide technical guidance to engineering teams.
- Ensure compliance with enterprise security and regulatory requirements.

📌 Data Architect (Hyderabad)
🏢 ValueLabs
📍 Hyderabad