Data & Research Analyst

Obviant•Arlington, VA

13d

About The Position

We're looking for a Research & Data Analyst to expand our core data platform. You'll be responsible for identifying, evaluating, and integrating new data sources and content into our platform—ensuring data is clean, structured, and ready to power analytics, context, and automation. This role combines deep research and analytical rigor with hands-on data work, requiring someone who can bridge business needs with technical execution.

Requirements

2-4 years of experience working with data in a research, analyst,, or business intelligence role
Strong SQL skills — Comfortable writing queries to join, filter, aggregate, and analyze data across multiple tables and sources
Data quality mindset — Track record of cleaning messy datasets, identifying data issues, and implementing validation checks
Problem-solving ability — Can navigate ambiguous situations, diagnose root causes, and develop practical solutions
Clear communicator — Able to explain technical concepts to non-technical audiences and document processes clearly
Basic scripting knowledge — Familiarity with Python, R, or similar tools for data manipulation is a plus but not required

Nice To Haves

Experience with BI tools — Hands-on use of Hex, Tableau, Looker, Power BI, or similar platforms to build dashboards and reports
Experience working with APIs or data integration platforms
Exposure to data warehouses (Snowflake, BigQuery, Redshift) or modern data stacks
Background in defense, govtech, or industries with complex data environments
Familiarity with data governance or master data management concepts

Responsibilities

Identify and Onboard New Data Sources: Lead exhaustive research to identify, evaluate, and obtain new OSINT sources. Establish and maintain relationships with third-party data providers to continuously expand platform capabilities.
Perform Strategic Research and Analysis: Conduct exhaustive research and advanced analysis, including writing SQL for quantitative conclusions and leading the qualitative analysis of unstructured sources (e.g., program documents) to extract nuance, intent, and context. This work establishes analytical frameworks, enables evidence-based decisions, and sets the foundation for all product features.
Clean and Structure Data for Production: Profile, validate, and work with engineering to transform raw, complex data into standardized formats that integrate seamlessly with our existing infrastructure and support automation.
Build and Maintain Data Workflows: Create and document repeatable processes for efficient data ingestion, comprehensive quality checks, and maintenance, ensuring the system can scale.
Create and Maintain a Data Audit Structure: Design and implement robust data checks within existing frameworks, performing cross-source comparisons to ensure absolute accuracy and data integrity.
Collaborate Across Teams: Serve as the go-to data domain expert, working closely with Product, Engineering, and Customer Success to translate customer needs into robust data solutions and inform the product roadmap. This includes creating quick-turnaround dashboards to test insights with real users before productization.
Document data assets — Create and maintain data dictionaries, lineage documentation, and process guides that enable teams to understand and use data effectively

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