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Data Architect strong Consulting

Job in Washington, District of Columbia, 20022, USA
Listing for: Xebia
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Engineer, Cloud Computing, Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Data Architect with strong experience in Consulting

With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition.

We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, Dev Ops, Data and AI, Cloud, Software Technology, Functional Programming, Low Code, and Microsoft.

We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services.

For more details, please visit

Job Title:

Data Architect with strong experience in Consulting

Location:

Washington, DC

Job Description:

-

We are seeking a Senior Data & Analytics Consultant with strong hands-on technology expertise and proven consulting experience. The candidate will lead Data & AI strategy initiative leveraging AWS and Snowflake
, while guiding the client through modern data architecture patterns including Lakehouse
, Open Table Formats (Delta / Iceberg), and AI-enabled use cases.

This is a client-facing role requiring strong stakeholder management, requirements gathering, and the ability to independently drive a consulting engagement end-to-end.

Key Responsibilities
  • Lead discovery workshops and requirement gathering sessions with business and technology stakeholders.
  • Translate business objectives into scalable data architecture and implementation roadmaps.
  • Drive engagement governance, solution articulation, and executive-level communication.
  • Provide thought leadership on modern data platform architecture and AI enablement.
  • Design and implement modern Data Warehouse and Lakehouse architectures
    .
  • Define data models (dimensional, normalized, Data Vault where appropriate).
  • Architect solutions using: (Good to have - will have Solution Architects supporting)
  • Snowflake (Data Warehouse, Snowpark, Streams/Tasks, Data Sharing)
  • Open table formats (Delta Lake / Apache Iceberg)
  • Recommend best practices for scalability, security, governance, and cost optimization.
  • Guide ingestion, transformation, and orchestration strategies.
  • Ensure implementation aligns with data governance and compliance standards.
4. AI & Emerging Technologies
  • Identify and design AI/ML enablement patterns (data readiness for ML, feature engineering pipelines).
  • Advise on modern data stack evolution including:
  • Lakehouse patterns
  • Data mesh principles (if applicable)
  • Evaluate new technologies and recommend adoption roadmap.
Required Skills & Experience Experience
  • 8+ years of total experience in Data Engineering / Data Architecture / Analytics Consulting.
  • Proven experience working in consulting engagements (client-facing).
  • Experience working with US-based clients is strongly preferred.
Technical Expertise
  • Strong hands-on experience with AWS data services.
  • Strong experience with Snowflake architecture and optimization.
  • Deep understanding of:
  • Data Warehousing concepts (dimensional modeling, performance tuning)
  • Lakehouse architecture patterns
  • Open table formats:
    Delta Lake and Apache Iceberg
  • Experience with cloud-native data pipelines and modern ELT frameworks.
  • Understanding of data governance, security, and compliance in cloud environments.
  • Exposure to AI/ML data pipelines and AI-driven analytics use cases.
Consulting & Soft Skills
  • Strong requirement gathering and stakeholder management skills.
  • Ability to articulate technical solutions to business leadership.
  • Experience driving projects independently.
  • Strong written and verbal communication skills.
  • Ability to operate in ambiguous environments typical of PE-backed portfolio transformations.
Preferred Qualifications
  • Experience working with Private Equity firms or portfolio companies.
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