Data Architect - Stafford / Quantico, VA

Yakshna Solutions, Inc.
Stafford
1 month ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

GCP Data Architect

Data Architect

Data Architect

We strive to attract and retain the brightest people and offer diverse job experiences with a full range of challenges and rewards.

We help companies realize and implement IT solutions strategically. Yakshna Solutions supports our clients' missions and goals by sharing our know-how, skills, and knowledge. We take pride in being an equal opportunity employer.

Working with Yakshna provides opportunities to develop your knowledge, skills, and abilities. You can also build a network of peers and mentors and advance your career! We offer exciting opportunities to work with industry experts, business consultants, and IT specialists across large government and private sector companies. Our diverse team recognizes the crucial importance of each individual to our success and offers competitive compensation, comprehensive benefits, and innovative training.

Opportunities exist across many services and US states. Remember to refer friends to earn cash for qualified referrals! Based on your profile and our current needs, our recruitment team will contact you.

Open Jobs

Jun 17 2025

ID

Job Title

Job Description

7611111 Data Architect

Yakshna Solutions, Inc (YSI) is a CMMI Level 3 assessed, ISO 9001, 20000:1, 27001 certified, woman-owned small business based in Herndon, Virginia. YSI provides professional IT solutions and services to corporations and government organizations. We are committed to serving our communities as a leading IT vendor offering innovative, quality, and cost-effective solutions.

Benefits include: 401(k), health, dental, vision insurance, life insurance, disability coverage, paid time off, and professional development support.

Job Responsibilities:

  • Develop data warehousing blueprints, evaluate hardware/software platforms, and integrate systems.
  • Assess reusability of current data for analysis.
  • Design data warehouses, including data design, database architecture, and metadata management.
  • Build relational databases, perform data access analysis, and design archive/recovery processes.
  • Review and develop object/data models and metadata repositories for better data management.
  • Knowledge of cybersecurity, privacy principles, networking, protocols, and risk management is required.
  • Maintain databases and optimize performance.
  • Understand database management systems, query languages, and data warehousing principles.
  • Manage physical and virtual data storage media.
  • Communicate effectively with team members and stakeholders.

Required Skills:

  • MS/MA in Computer Science with 10 years’ experience or BA/BS with 12 years’ experience in data management, programming, and architecture.
  • Eligibility for Top Secret clearance with completed T5 investigation.
  • Must hold four Microsoft Certifications from specified options, including Azure and Security certifications.
  • Alternatively, at least one role-based Microsoft Certification or Data Science certification.

YSI is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, veteran status, or disability.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.