Learn and understand a broad range of DHHSs data resources and their business application domains.
Drive digital transformation initiatives across the program.
Recognize and adopt best practices in data transformation: data integrity, test design, analysis, validation, and documentation.
Design, implement, and support a platform providing secured access to large datasets.
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Provide advanced data support to data engineering and ETL teams.
Extract and evaluate data to ensure accurate mapping for end user consumption.
Collaborate with technical support teams and business process owners to ensure seamless operations service delivery.
Develop processes and procedures to enhance the quality and efficiency of quality control checks in the production environment.
Create and implement plans to improve data quality by identifying causes of errors or discrepancies and devising effective solutions.
Establish robust procedures for data collection and analysis.
Programmatically manipulate and analyze large datasets, build data pipelines, and automate tasks.
Design and maintain efficient data processing flows.
Support test readiness reviews, test planning work groups, and pre and post test briefings.
Communicate issues effectively in writing and orally to executive audiences, business stakeholders, and technical teams.
Support the technical and operational architecture of complex enterprise systems.
Tune application and query performance using profiling tools and SQL.
Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using Azure and / or AWS / public cloud tools.