FDA · 3 hours ago

Business Informaticist (Data Integration)

United States

Full-time

Remote

Mid Level

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Responsibilities

Design, develop, and maintain ETL processes to extract data from various sources, transform it into a usable format using enterprise platforms, and load into data warehouses or data lakes.

Integrate and consolidate data from multiple sources utilizing data integration tools (e.g., Informatica, DataBricks, AWS Glue, AWS Kinesis, Redshift), ensuring consistency and accuracy of data.

Identify and resolve performance issues within ETL processes to ensure efficient data extraction and transformation. The incumbent implements data quality checks and validation procedures to maintain data integrity.

Create and maintain data models using available data modeling tools (e.g., Erwin, SPARX, Prolaborate).

Create and maintain documentation of ETL processes and data/meta-data lineage.

Understand and apply Master Data Management (MDM) concepts to data domains. Utilize skills in match-merge, text matching, ontologies, and standard terminology libraries/crosswalks to mature MDM activities.

Collaborate with business users to understand data requirements and ensure ETL solutions meet business needs.

Manage and make recommendations for improvement of the ETL framework to support scalability and sustainability. As well as resolves ETL-relates issues in a timely manner.

Qualification

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ETL processesData integration toolsData modeling toolsMaster Data ManagementData quality checksData analyticsDocumentation

Required

Design, develop, and maintain ETL processes to extract data from various sources, transform it into a usable format using enterprise platforms, and load into data warehouses or data lakes.

Integrate and consolidate data from multiple sources utilizing data integration tools (e.g., Informatica, DataBricks, AWS Glue, AWS Kinesis, Redshift), ensuring consistency and accuracy of data.

Identify and resolve performance issues within ETL processes to ensure efficient data extraction and transformation.

Implement data quality checks and validation procedures to maintain data integrity.

Create and maintain data models using available data modeling tools (e.g., Erwin, SPARX, Prolaborate).

Create and maintain documentation of ETL processes and data/meta-data lineage.

Understand and apply Master Data Management (MDM) concepts to data domains.

Utilize skills in match-merge, text matching, ontologies, and standard terminology libraries/crosswalks to mature MDM activities.

Collaborate with business users to understand data requirements and ensure ETL solutions meet business needs.

Manage and make recommendations for improvement of the ETL framework to support scalability and sustainability.

Resolve ETL-related issues in a timely manner.