Senior Data Platform & AI Lead

Strategic Growth Partners; Washington (District of Columbia); Hybrid; USD 83,000 - 165,000; Full time

Job summary

Strategic Growth Partners seeks a senior Data Platform Architect to lead modernization across multi-cloud environments, delivering scalable, compliant data and AI platforms.

You will collaborate with DoD-focused programs, governance, and cross-domain access while guiding vendors and internal teams. Willingness to travel up to 80% and active Secret clearance are required.

Qualifications

• 10+ years of professional experience in data platform architecture and/or AI/ML engineering for large enterprises, with consulting or advisory delivery.
• Experience leading data platform modernization and AI/ML enablement programs.
• Government or defense experience strongly preferred; regulated industry experience can substitute.
• Cloud data or ML certifications strongly preferred.
• Willingness to travel up to 80% and ability to work in DoD/commercial environments.

Responsibilities

• Lead data platform architecture and modernization roadmaps across hybrid/multi-cloud environments.
• Design AI/ML enablement architectures for scalable model development, deployment, and monitoring.
• Assess governance readiness and develop implementation roadmaps aligned with compliance timelines.
• Define data foundation scope including ownership and governed access.
• Support practice development through internal training and content creation.

Skills

Data platform architecture

ETL/ELT design

AI/ML platform

Data governance

Cloud data infra

Data security

DoD data

Sovereign AI hosting

Data classification

DataMesh

Vendor negotiation

Scalable data platform

Federal contracting

GenAI integration

Education

Bachelor's degree

Advanced degree preferred

Certifications in Cloud/ML (AWS, Azure, GCP, Databricks)

Tools

Snowflake

Databricks

BigQuery

Redshift

Job description

Strategic Growth Partners provides both operations and strategic support to commercial organizations. Our client is a leading global professional services firm dedicated to helping organizations tackle their most complex business issues, maximize stakeholder value, and deliver sustainable change.

Workplace Type:

80% travel. Hybrid.

Employment Type:

Full-Time

Clearance:

Active Secret Clearance required; TS/SCI eligibility strongly preferred.

Compensation:

Hourly rate is DOE.

Experience Should Include:

• Modern data platform architecture, including data lakes, lakehouses, and cloud data warehousing (Snowflake, Databricks, BigQuery, Redshift).
• Data pipeline and ETL/ELT design, orchestration tooling, and data integration across structured and unstructured sources.
• AI/ML platform engineering, including MLOps, model deployment pipelines, feature stores, and LLM/GenAI platform integration.
• Data governance, lineage, cataloging, and metadata management frameworks.
• Cloud data infrastructure across AWS, Azure, and/or GCP, including cost modeling and platform consolidation.
• Data security, privacy, and regulatory compliance. Direct experience with DoD data and cloud policy (for example, the DoD Data Strategy and cloud impact levels IL4 to IL6) is a strong advantage and preferred for this role; GDPR, CCPA, or industry-specific data regulation can substitute.
• AI-driven data engineering. Baseline competency with AI-assisted development, testing, and monitoring tools is expected; candidates should articulate how AI accelerates platform build and data operations.
• Negotiating with data and AI platform vendors and general understanding of commercial models and licensing structures, including competing vendors and avoiding sole-source dependence.
• Designing and architecting highly available, scalable data platforms with proven experience in real-time and batch processing, disaster recovery, and multi-region redundancy.
• Federal contracting experience.
• Sovereign AI hosting, including running LLMs and the data they access inside controlled boundaries, with consideration for high-density GPU compute and low-latency networking needs.
• Data classification and cross-boundary or cross-domain data movement, ensuring users and AI agents see only approved data at the appropriate impact levels.
• Data ownership, taxonomy, and governed access across a large federated organization, including stewardship roles.
• Data mesh/federated data architecture (for example, DataMesh) that collects and connects data from multiple Military Departments (MilDeps), while keeping domain ownership with each MilDep and enforcing common standards, catalogs, and access policies.

Responsibilities:

• Lead data platform architecture and engineering assessments, including current-state analysis, target-state design, and modernization roadmaps.
• Design AI/ML enablement architectures that support scalable model development, deployment, and monitoring across hybrid and multi-cloud environments.
• Assess data governance and AI readiness and develop implementation roadmaps aligned with compliance and business timelines.
• Evaluate dependencies between data platform modernization and AI/ML initiative sequencing.
• Assess AI infrastructure readiness, including compute, power, networking, and hosting boundaries, alongside the data center and network leads.
• Define the data foundation scope, including ownership, taxonomy, governed access, and integrated reporting, and identify where in-flight programs can be accelerated. This includes the federated data model (DataMesh) for collecting and connecting data across MilDeps, covering domain data products, interoperability standards, and cross-MilDep access.
• Define and integrate findings into A&M's broader engagement scope and deliverables.
• Support practice development through internal training, content creation, and people development.

Qualifications:

• 10+ years of professional experience in data platform architecture and/or AI/ML engineering for complex, large enterprises, with consulting or advisory delivery experience.
• Demonstrated experience leading data platform modernization, AI/ML enablement, or data-driven transformation programs.
• Government or defense experience strongly preferred. Regulated industry experience in financial services or healthcare can substitute; deep transformation experience in other complex environments may also substitute.
• Bachelor's degree required; an advanced degree in a technical field is a plus. Cloud data or ML certifications (AWS, Azure, GCP, Databricks) are strongly preferred.
• Comfortable with travel up to 80%.
• Active Secret Clearance required; TS/SCI eligibility strongly preferred.
• U.S. Citizenship and Residency required.

What Distinguishes a Great Candidate:

Has designed and implemented large-scale, highly complex data and AI platform transformations — not just operated existing pipelines and models. Understands the dependency between data platform readiness and AI/ML program success. Can work across data engineering, AI/ML, security, and business stakeholder teams. Brings AI-assisted platform engineering into the delivery toolkit as standard practice. Has worked with classified or cross-boundary data and understands how it constrains platform and AI design.