Job Description

Technical Responsibilities

• Build and maintain out of standards data models to report disparate data sets in a reliable, consistent and interpretable manner.
• Gather, distil and harmonize data requirements and to design coherent Conceptual, logical and physical data models and associated physical feed formats to support these data flows.
• Articulate business requirements and build source-to-target mappings having complex ETL transformation. Able to handle the end-to-end ETL or ELT pipeline solely.
• Write complex SQL statements and profile source data to validate data transformations.
• Contribute to requirement analysis and database design - Transactional and Dimensional data modelling.
• Normalize/ De-normalize data structures, introduce hierarchies and inheritance wherever required in existing/ new data models.
• Develop and implement data warehouse/Data Lake projects independently.
• Work with data consumers and data suppliers to understand detailed requirements, and to propose standardized data models.
• Contribute to improving the Data Management data models.
• Be an influencer to present and facilitate discussions to understand business requirements and develop dimensional data models based on these capabilities and industry best practices.
• Extensive practical experience in Information Technology and software development projects of with at least 5+ years of experience in developing data warehouse, data lake, data platform systems
• Strong understanding of implementing multiple Data Programs viz.
• Data Lakehouse, Data Warehouse, Advanced Analytics, Master Data Management, Data Modelling, Analytics and Virtualization.

Requirements

• Extensive experience in on cloud data technologies in particular on AWS or Azure.
• Strong experience in established data technologies viz. Data ingestion, ETL, and data warehouse, CDC and Event Streaming technologies.
• Hands on experience in design and implementation of data pipelines, ETL and data warehouse/lake technologies following industry standards
• Ability to write complex SQL for data transformations and data profiling in source and target systems
• Strong understanding of SQL vs NoSQL databases.
• Industry experience in defining & implementing solution using data integration technologies
• Experienced or conversant in emerging tools like parquet and iceberg, databases, and unstructured data. Must understand them sufficiently to guide the organization in understanding and adopting them
• Possess a combination of solid business knowledge and technical expertise with strong communication skills.
• Demonstrate excellent analytical and logical thinking.
• Good verbal & written communication skills and Ability to work independently as well as in a team environment providing structure in ambiguous situation.

Good to have

• Understanding of Insurance/Banking Domain
• Understanding of AWS/Azure cloud
• Good understanding of Master Data Management, Data Quality and Data Governance.
• Basic understanding of data visualization tools like Power BI, Tableau
• Good understanding of implementing & architecting data solutions using the informatica, SQL server/Oracle