Data Architect (Immediate)

This is an immedaite requirement, hence immediate joiners and candidates who can join within 30 days will be given higher preference.

We are seeking a Data Architect with deep experience designing and implementing scalable, secure, and high-performance cloud data platforms. Ideal candidates will have solid Databricks expertise, strong knowledge of Azure data services, and hands-on architecture experience building modern data ecosystems including big data, metadata management, and enterprise-grade data governance. The Data Architect will collaborate closely with customers to define architectural blueprints, guide engineering teams, and ensure robust data solutions that support analytics, reporting, and advanced AI workloads.

Key Responsibilities

• Design and lead end-to-end architecture for complex cloud-based data ecosystems, including lakehouse and enterprise data platforms.
• Translate business requirements into scalable architectural designs, roadmaps, and technical specifications, including advanced scenarios, such as establishing common data models across development teams, sharing multi-tenant system data directly to customers, integrations between Databricks and external data platforms, and handling RLS from Databricks source data to analytics and reporting tools.
• Architect and implement Databricks-based solutions, including Unity Catalog, Delta Lake, Databricks SQL, Workflows, and governance frameworks. Establish data governance policies in addition to technical solutions.
• Define and enforce data modelling standards for relational, dimensional, and lakehouse structures, including common data models across global systems.
• Architect and oversee development of ETL/ELT frameworks, source-to-target mappings, and reusable transformation standards, focusing on meta-data solutions.
• Establish best practices for data ingestion, curation, cataloging, lineage, quality, and MDM across the data ecosystem. Establish MDM solutions, preferably with Profisee.
• Partner with cross-functional engineering teams to ensure architectural consistency, performance optimization, and security compliance.
• Mentor and lead junior engineers, contributing to technical direction, design reviews, and architectural decision-making.
• Develop cloud-native reference architectures leveraging Azure Data Factory, Azure SQL, Synapse Analytics, Azure Data Lake, Stream Analytics, and other modern Azure services.
• Collaborate with executive and architect stakeholders to define data governance standards, taxonomy structures, and metadata strategies. Explain and defend architecture decisions to customers.

Minimum Qualifications

• Bachelors Degree in Computer Science, Engineering, MIS, or a related field.
• 12+ years of experience in total along with strong data engineering or data platform development background and with at least 3+ years in data architecture roles.
• 3+ years of experience with Databricks, including Unity Catalog, Delta Lake, Databricks SQL, and Workflow orchestration.
• Strong proficiency with Python, Apache Spark, and distributed data processing frameworks.
• Advanced SQL expertise, including performance tuning, indexing, and optimization for large datasets.
• Proven experience designing and implementing lakehouse architectures and cloud data ecosystems.
• Hands-on experience with Azure Data Services: ADF, ADLS, Azure SQL, Synapse Analytics, Stream Analytics or Fabric equivalents.
• Strong understanding of data modelling principles (3NF, dimensional modelling, Kimball, Inmon) and enterprise data warehouse concepts.
• Prior consulting experience delivering analytics or data platform solutions to enterprise clients.
• Familiarity with CI/CD pipelines and IaC tools (Terraform, ARM, Bicep).

Preferred Qualifications

• Demonstrate examples of creating the strategy and implementing infrastructure to support different environments using automation of CI/CD pipelines, GIT, and other tools.
• Experience with Microsoft Fabric or other emerging cloud analytics platforms.
• Exposure to Big Data platforms (HDFS, Hive, Pig, MapReduce) and general DBMS systems (Oracle, DB2, MySQL).
• Exposure to NoSQL ecosystems such as Cassandra, MongoDB, HBase, CouchDB.
• Experience with BI and reporting tools (Power BI, Qlik, Tableau, Cognos, MicroStrategy).