Technical Data Analyst

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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long term project. Here are a few details.

Requirements

We are seeking a seasoned Technical Data Analyst to join our team on‑site in McLean, VA. In this role, you will collaborate with Agile delivery teams to mine, analyze, and translate complex data into actionable business insights that inform decision‑making. You’ll work hands‑on with SQL and Python, author user stories in Jira, and interface directly with stakeholders to ensure data integrity, completeness, and timeliness.

Key Responsibilities

• Data Extraction & Transformation
  

  • Author, optimize, and maintain complex SQL queries, views, and stored procedures against large relational databases.
    

  • Develop and execute Python scripts via the command line to automate data ingestion, transformation, and validation tasks.
    

  • Navigate log directories, parse and analyze application logs to troubleshoot data pipeline issues.
    

• Agile Delivery & Documentation
  

  • Partner with Product Owners and Scrum Masters to elicit business and technical requirements.
    

  • Create and manage detailed user stories, acceptance criteria, and technical tasks in Jira.
    

  • Participate in sprint ceremonies (planning, stand‑ups, retrospectives, demos) and adhere to team Definition of Done.
    

• Data Analysis & Insights
  

  • Perform exploratory data analysis across disparate data sources—structured, semi‑structured, and unstructured—to identify trends, anomalies, and data quality issues.
    

  • Build dashboards, reports, and visualizations that clearly communicate key performance indicators and business metrics.
    

  • Present findings and recommendations to both technical and non‑technical stakeholders, tailoring communications to the audience.
    

• Business Translation & Support
  

  • Translate high‑level business requirements into detailed technical specifications and data rules.
    

  • Serve as a liaison between business SMEs and engineering teams to ensure alignment on data definitions, data models, and deliverables.
    

  • Adapt quickly to evolving priorities and pivot analysis plans to meet tight deadlines and changing business needs.
    

• Quality & Continuous Improvement
  

  • Proactively identify opportunities to improve data workflows, reduce manual effort, and enhance data quality.
    

  • Implement best practices for version control, code reviews, and documentation.
    

  • Mentor junior data analysts on SQL, Python scripting, and Agile processes.
    

Required Qualifications

• Experience:
  

  • Minimum 8 years in Data Analytics, Data Mining, or Data Science roles, supporting large‑scale enterprise environments.
    

  • Prior experience with Freddie Mac or similar financial services clients is strongly preferred.
    

• Technical Skills:
  

  • SQL: Expert‑level proficiency writing, tuning, and debugging queries in Oracle, SQL Server, or similar RDBMS.
    

  • Python: Comfortable executing scripts from the command line; experience with core libraries (pandas, NumPy) a plus.
    

  • Agile/Jira: Proven track record working in Scrum/Agile teams; capable of drafting clear user stories and technical tasks.
    

• Analytical & Problem‑Solving:
  

  • Exceptional ability to dissect multifaceted data sets, distill insights, and formulate data‑driven recommendations.
    

  • Demonstrated skill in translating non‑technical business objectives into technical requirements and data rules.
    

• Communication & Collaboration:
  

  • Strong verbal and written communication skills; adept at presenting complex information to diverse audiences.
    

  • Team player with a flexible mindset—able to reprioritize tasks rapidly in response to shifting business drivers.
    

• Location & Availability:
  

  • Must be local to the VA, DC, or MD area and available to work 100 % on‑site in McLean, VA.
    

  • Any valid U.S. work visa status is acceptable.
    

Nice‑to‑Have

• Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
  

• Familiarity with version control systems (Git) and CI/CD pipelines (e.g., Jenkins).
  

• Background in financial products, mortgage servicing, or credit risk analytics.
  

• Basic understanding of cloud‑based data platforms (AWS Redshift, Azure Synapse).
  

Benefits