Principal Databricks Data Engineer

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

Key Requirements

• Experience in enterprise Data Warehouse and Data Lake platforms
• Hands‑on experience with Databricks and Spark at scale
• Strong experience in modernizing legacy Cloudera platforms (CDH/CDP, Hive, HBase, Impala, Spark) to Databricks Lakehouse
• Redesign ingestion, transformation, and consumption patterns from HDFS‑based architecture to cloud object storage and Delta Lake
• Refactor legacy Hive/Impala logic into PySpark and Spark SQL ELT pipelines
• Ensure data reconciliation, audit integrity, and consistency during migration
• Design and govern enterprise Data Warehouse and Data Lake/Lakehouse architectures
• Implement layered architecture including Raw/Landing, Curated/Conformed, and Semantic/Consumption layers
• Modernize traditional EDW platforms into scalable lakehouse architectures
• Strong experience in finance and risk data models including General Ledger, Sub‑ledger, financial hierarchies, and risk exposure models (credit, liquidity, market risk)
• Enable reporting use cases including aggregation, drill‑down, and drill‑back capabilities
• Build and manage semantic/consumption layers for BI, reporting, and analytics
• Define business metrics, dimensions, hierarchies, and KPIs
• Experience with Databricks SQL, Delta tables, and dbt or similar frameworks
• Develop and optimize large‑scale data pipelines using PySpark, Spark SQL, and Delta Lake
• Optimize workloads using Z‑ORDER, OPTIMIZE, caching, and cluster configurations
• Implement data governance, data quality frameworks, reconciliation controls, and exception handling
• Establish data lineage and metadata management
• Ensure data security, access control, and compliance standards
• Experience with cloud platforms such as AWS or Azure
• Experience with CI/CD pipelines using Git, Terraform, Jenkins, or Azure DevOps
• Familiarity with orchestration tools such as Airflow or Databricks Workflows
• Experience with dbt is a plus
• Act as a technical authority and lead architecture decisions
• Mentor and guide senior engineers and establish engineering standards
• Strong stakeholder management with finance, risk, analytics, and governance teams
• Ability to translate complex data structures into business‑ready insights

Nice to Have

• Experience in BFSI, Capital Markets, or regulatory reporting
• Exposure to SAP Finance, Oracle Financials, or S/4HANA
• Experience supporting AI/ML workloads
• Databricks or cloud certifications

Impact

• Lead Cloudera to Databricks transformation initiatives
• Shape enterprise finance and risk data platforms
• Support regulatory, management, and analytical reporting systems

Salary Range

CA$ 100,000 – CA$ 120,000 Per Year