Description

You will architect and lead enterprise data solutions, focusing on scalable data lakes, warehousing, and real-time streaming pipelines.

Responsibilities

• Design and implement enterprise-wide data architecture, including data migration, transformation, and warehouse/mart builds.
• Build and maintain high-performance data pipelines using Spark, Scala, and Databricks with Delta Lake and Delta Live Tables.
• Manage structured streaming and batch systems, handling late data, windowing definitions, and data freshness strategies.
• Optimize SQL queries, RDBMS schemas, indexing, and partitioning for large-scale data operations.
• Lead system integration efforts and troubleshoot complex technical issues across the data stack.

Required Skills

• 6-8 years of IT experience in enterprise data architecture and management.
• Expertise in Conceptual, Logical, and Physical Data Modelling (Relational and Dimensional).
• Proficiency with Databricks (on-prem and cloud), Spark Scala, and Delta Lake concepts.
• Advanced SQL skills including joins, aggregation, windowing functions, and CTEs.
• Experience with ETL/ELT tools such as Data Migration Service.
• Understanding of incremental data loads (tumbling/sliding windows, high watermark).
• Familiarity with Schema Registry and message formats (Avro, ORC).

Preferred Skills

• Experience with AWS Lambda, S3, and CloudWatch for serverless processing and monitoring.
• Familiarity with GitLab for CI/CD pipeline maintenance.
• Experience with data quality frameworks like Great Expectations.

Key Skills

Education

Any Graduate