- Experience in SQL Server databases, Oracle and/or cloud databases.

- Experience in data warehousing and data mart, Star and Snowflake model.

- Experience in loading data into database from databases and files.

- Experience in analyzing and drawing design conclusions from data profiling results.

- Understanding business process and relationship of systems and applications.

- Must be comfortable conversing with the end-users.

- Must have ability to manage multiple projects/clients simultaneously.

- Excellent analytical, verbal and communication skills.

Role and Responsibilities :

- Work with business stakeholders and build data solutions to address analytical & reporting requirements.

- Work with application developers and business analysts to implement and optimise Databricks/AWS-based implementations meeting data requirements.

- Design, develop, and optimize data pipelines using Databricks (Delta Lake, Spark SQL, PySpark), AWS Glue, and Apache Airflow

- Implement and manage ETL workflows using Databricks notebooks, PySpark and AWS Glue for efficient data transformation

- Develop/ optimize SQL scripts, queries, views, and stored procedures to enhance data models and improve query performance on managed databases.

- Conduct root cause analysis and resolve production problems and data issues.

- Create and maintain up to date documentation of the data model, data flow and field level mappings.

- Provide support for production problems and daily batch processing.

- Provide ongoing maintenance and optimization of database schemas, data lake structures (Delta Tables, Parquet), and views to ensure data integrity and performance