Lead Data Engineer

iAdeptive is looking for a data engineer who has architected and operated distributed data platforms at scale — and can prove it in code, commits, and production incidents survived. You will embed deeply with federal clients as their data architecture lead, own iAdeptive's data platform strategy from design through delivery, and build the federated architecture that powers AI and analytics across mission programs.

HANDS-ON FIRST

You design the data mesh and you implement the first domain. You define the data contract standard and you write the first contract. You own problems end-to-end — picking up whatever knowledge you're missing to get the job done. Real delivery is your credibility.

AI-AUGMENTED, NOT AI-DEPENDENT

You use AI tools to accelerate pipeline development, documentation, and schema generation. You do not let generated code enter production without review. You understand what the query plan says, why the lineage graph matters — and you document your architecture decisions formally.

TREND LEADER

You track what Databricks, dbt Labs, Snowflake, and the open table format ecosystem are shipping. You have opinions on Unity Catalog vs. Iceberg vs. Hudi. You bring those opinions to iAdeptive's roadmap before clients ask — not after.

What You Will Do

• Deeply embed with federal clients as the data architecture lead — partnering with technical teams, subject matter experts, and implementation partners from prototype through production
• Work with senior stakeholders to identify the highest-value data applications and build a prioritized, comprehensive data backlog supporting their AI and analytics roadmap
• Architect and implement a federated Data Mesh across federal program domains, establishing domain ownership and data product standards
• Design and build modern lakehouse solutions using open table formats (Iceberg, Delta Lake, Hudi) on cloud and on-premise infrastructure
• Define and enforce data contracts, SLAs, and data-as-a-product standards; develop Data Architecture Decision Records (ADRs) for key platform choices
• Implement data lineage, observability, and quality frameworks meeting federal audit, FISMA, and compliance requirements
• Apply privacy-by-design principles throughout the data platform lifecycle; implement data classification, access controls, and sensitive data handling aligned with federal privacy law
• Build and manage Canonical Data Environments (CDEs) with cross-system reconciliation and master data management
• Develop data governance artifacts: data dictionaries, lineage maps, quality scorecards, and use-case inventories
• Partner with the AI engineering lead to ensure data platform quality, lineage, and governance supports model training and inference pipelines
• Drive multiple concurrent data workstreams and prioritize ruthlessly across competing client and internal demands
• Mentor engineers; codify best practices and publish reusable pipeline templates and governance playbooks

What We're Looking For

• 8+ years of data engineering experience with 3+ years in senior or lead architecture roles
• Hands-on experience designing and implementing Data Mesh architectures with domain-owned data products
• Deep proficiency in modern lakehouse tooling: Apache Iceberg, Delta Lake, Apache Hudi, or equivalent
• Strong SQL, Python, and at least one orchestration framework (Airflow, Prefect, Dagster)
• Experience with data quality frameworks, metadata management, and data lineage tooling (OpenMetadata, Apache Atlas, or equivalent)
• Knowledge of cloud data platforms: AWS (Glue, Athena, Redshift), Azure (Fabric, Synapse), or GCP (BigQuery, Dataproc)
• Understanding of federal data governance, privacy requirements, and data classification frameworks
• Understanding of network and cloud architecture including on-premise and hybrid deployments
• Proven high-throughput operator — drives multiple concurrent projects and prioritizes ruthlessly
• Effective communicator who translates data architecture decisions to senior federal stakeholders and implementation partners
• Bachelor’s degree required; advanced degree preferred
• We offer remote flexibility, with a preference for candidates local to Maryland.

Bonus Points

• Federal contracting or public sector implementation experience (U.S. federal preferred)
• Active security clearance or ability to obtain one (TS/SCI a significant plus)
• Experience with sensitive data domains: healthcare (HIPAA), defense, or financial data
• Familiarity with FedRAMP, FISMA, or federal data classification frameworks
• Founding engineer or startup experience — people who have built something from zero
• Experience building or governing master data management (MDM) systems

Competencies & What They Look Like at iAdeptive

Competency

What It Looks Like at iAdeptive

Technical Credibility

Earns trust by shipping — designs the architecture, implements the first domain, and proves it in production metrics.

Strategic Thinking

Translates federal mission data needs into actionable platform roadmaps and prioritized, funded backlogs.

Data Stewardship

Champions privacy-by-design, data quality, and governance as first-class engineering concerns — not afterthoughts.

Stakeholder Influence

Communicates data architecture trade-offs clearly to engineers, program offices, and federal executives.

Accountability

Owns platform decisions end-to-end; maintains ADRs, lineage documentation, and quality scorecards with rigor.

Adaptability

Tracks the open table format and data mesh ecosystem; adjusts iAdeptive's platform approach before clients ask.

Collaboration

Partners with AI engineering, federal clients, systems integrators, and cross-domain data owners to deliver integrated solutions.

Why iAdeptive

Federal data is complex, high-stakes, and architecturally challenging — the kind of problem that keeps great data engineers engaged for years. You will have direct influence over platform decisions, own your domain end to end, and build something that matters for real mission programs.

Job Type: Full-time

Pay: From $130,000.00 per year

Benefits:

• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Professional development assistance
• Vision insurance

Education:

• Bachelor's (Required)

Experience:

• data engineering: 8 years (Required)

Work Location: Hybrid remote in Columbia, MD 21046