Data Architect

ValueLabs; Hyderabad; On-site; INR 3,000,000 - 7,000,000; Full time

Job summary

ValueLabs is seeking an experienced Senior Data Platform Architect to design, implement, and govern scalable data platforms supporting analytics, AI/ML, and BI initiatives. The role requires deep Databricks expertise, data modeling, cloud data engineering, and architecture best practices.

You will lead enterprise data architecture and collaborate with data engineers, analysts, and data scientists. Location is Hyderabad, India, with opportunities to influence global data strategy and drive

Qualifications

• 10 to 14 years of relevant experience in data engineering/data platforms.
• Expertise in Databricks Lakehouse Platform and Spark (PySpark/Scala).
• Strong knowledge of data governance, security, and compliance.
• Experience with cloud platforms (Azure preferred, AWS, GCP).

Responsibilities

• Define and implement enterprise-wide data architecture strategies.
• Design scalable 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 modern data architectures.
• Define data governance, metadata management, data quality, lineage, and security standards.
• Collaborate with business stakeholders, data engineers, analysts, and data scientists to translate requirements 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.

Skills

Databricks Lakehouse Platform

Apache Spark (PySpark/Scala)

Delta Lake/Unity Catalog/Delta Live

Databricks Workflows

Data warehousing & dimensional models

Cloud platforms: Azure/WAS/ GCP

SQL & performance tuning

ETL/ELT frameworks

Data governance & security

DevOps/CI-CD / IaC (Terraform)

BI tools: Power BI/Tableau/Looker

Tools

Terraform

Databricks

Power BI

Tableau

Looker

Job description

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

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.
• 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

• Lakehouse Architecture.
• Data Mesh / Data Fabric concepts.
• Master Data Management (MDM).
• Metadata Management.
• Data Governance.
• 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 modern 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.