Scope of Responsibilities
- Define and lead Govini's data lifecycle strategy across data acquisition, data ingestion, data cleansing, normalization and linkage.
- Ensure key entities within datasets are identified, resolved and linked to existing entities within the current master data repository.
- Apply various techniques to produce solutions to large-scale optimization problems, including data pre-processing, indexing, blocking, field and record comparison and classification.
- Improve data sharing, increase data repurposing and improve cost efficiency associated with data management efforts.
- Build best practices that help with chain of custody of data so it can be easily traced back to the source for accuracy and consistency.
- Work across functional teams to understand advanced statistical, machine learning, and text processing models and incorporate them into Govini’s existing data engineering infrastructure.
- Perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns.
- Work directly with users as well as SMEs to establish, create and populate optimal data architectures and structures, as well as articulate techniques and results using non-technical language.
Qualifications
- U.S. Citizenship is required
- Bachelor's degree in Computer Science, Mathematics or a related technical field
- 3-5 years experience with programmatically transforming data
- Experience with RDBMS
- Advanced SQL programming skills
- Proficient usage of common data formats such as CSV, XML, and JSON
- Requires strong analytical ability and attention to detail
- Ability to work independently with little supervision
- A burning desire to tackle hard problems and create sustainable solutions
- Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Experience using Amazon Web Services
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Working knowledge with large (multiple terabytes) amounts of data
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