{"schemaVersion":"jobsearcher.job.v1","id":"6e42c542f21d6ea23d3b9d68","url":"https://jobsearcher.com/jobs/6e42c542f21d6ea23d3b9d68","canonicalUrl":"https://jobsearcher.com/jobs/6e42c542f21d6ea23d3b9d68","title":"Lead Data Engineer","description":"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.\nHANDS-ON FIRST\nYou 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.\nAI-AUGMENTED, NOT AI-DEPENDENT\nYou 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.\nTREND LEADER\nYou 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.\nWhat You Will Do\nDeeply embed with federal clients as the data architecture lead — partnering with technical teams, subject matter experts, and implementation partners from prototype through production\nWork with senior stakeholders to identify the highest-value data applications and build a prioritized, comprehensive data backlog supporting their AI and analytics roadmap\nArchitect and implement a federated Data Mesh across federal program domains, establishing domain ownership and data product standards\nDesign and build modern lakehouse solutions using open table formats (Iceberg, Delta Lake, Hudi) on cloud and on-premise infrastructure\nDefine and enforce data contracts, SLAs, and data-as-a-product standards; develop Data Architecture Decision Records (ADRs) for key platform choices\nImplement data lineage, observability, and quality frameworks meeting federal audit, FISMA, and compliance requirements\nApply privacy-by-design principles throughout the data platform lifecycle; implement data classification, access controls, and sensitive data handling aligned with federal privacy law\nBuild and manage Canonical Data Environments (CDEs) with cross-system reconciliation and master data management\nDevelop data governance artifacts: data dictionaries, lineage maps, quality scorecards, and use-case inventories\nPartner with the AI engineering lead to ensure data platform quality, lineage, and governance supports model training and inference pipelines\nDrive multiple concurrent data workstreams and prioritize ruthlessly across competing client and internal demands\nMentor engineers; codify best practices and publish reusable pipeline templates and governance playbooks\nWhat We're Looking For\n8+ years of data engineering experience with 3+ years in senior or lead architecture roles\nHands-on experience designing and implementing Data Mesh architectures with domain-owned data products\nDeep proficiency in modern lakehouse tooling: Apache Iceberg, Delta Lake, Apache Hudi, or equivalent\nStrong SQL, Python, and at least one orchestration framework (Airflow, Prefect, Dagster)\nExperience with data quality frameworks, metadata management, and data lineage tooling (OpenMetadata, Apache Atlas, or equivalent)\nKnowledge of cloud data platforms: AWS (Glue, Athena, Redshift), Azure (Fabric, Synapse), or GCP (BigQuery, Dataproc)\nUnderstanding of federal data governance, privacy requirements, and data classification frameworks\nUnderstanding of network and cloud architecture including on-premise and hybrid deployments\nProven high-throughput operator — drives multiple concurrent projects and prioritizes ruthlessly\nEffective communicator who translates data architecture decisions to senior federal stakeholders and implementation partners\nBachelor’s degree required; advanced degree preferred\nWe offer remote flexibility, with a preference for candidates local to Maryland.\nBonus Points\nFederal contracting or public sector implementation experience (U.S. federal preferred)\nActive security clearance or ability to obtain one (TS/SCI a significant plus)\nExperience with sensitive data domains: healthcare (HIPAA), defense, or financial data\nFamiliarity with FedRAMP, FISMA, or federal data classification frameworks\nFounding engineer or startup experience — people who have built something from zero\nExperience building or governing master data management (MDM) systems\nCompetencies & What They Look Like at iAdeptive\nCompetency\nWhat It Looks Like at iAdeptive\nTechnical Credibility\nEarns trust by shipping — designs the architecture, implements the first domain, and proves it in production metrics.\nStrategic Thinking\nTranslates federal mission data needs into actionable platform roadmaps and prioritized, funded backlogs.\nData Stewardship\nChampions privacy-by-design, data quality, and governance as first-class engineering concerns — not afterthoughts.\nStakeholder Influence\nCommunicates data architecture trade-offs clearly to engineers, program offices, and federal executives.\nAccountability\nOwns platform decisions end-to-end; maintains ADRs, lineage documentation, and quality scorecards with rigor.\nAdaptability\nTracks the open table format and data mesh ecosystem; adjusts iAdeptive's platform approach before clients ask.\nCollaboration\nPartners with AI engineering, federal clients, systems integrators, and cross-domain data owners to deliver integrated solutions.\nWhy iAdeptive\nFederal 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.\nJob Type: Full-time\nPay: From $130,000.00 per year\nBenefits:\n401(k) matching\nDental insurance\nHealth insurance\nLife insurance\nPaid time off\nProfessional development assistance\nVision insurance\nWork Location: Hybrid remote in Columbia, MD 21046","company":"Iadeptivetechnologies","rawCompany":"iadeptivetechnologies","city":"Columbia","state":"MD","isRemote":false,"isActive":false,"createdAt":"2026-07-16T17:59:30.686Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Lead Data Engineer","description":"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.\nHANDS-ON FIRST\nYou 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.\nAI-AUGMENTED, NOT AI-DEPENDENT\nYou 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.\nTREND LEADER\nYou 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.\nWhat You Will Do\nDeeply embed with federal clients as the data architecture lead — partnering with technical teams, subject matter experts, and implementation partners from prototype through production\nWork with senior stakeholders to identify the highest-value data applications and build a prioritized, comprehensive data backlog supporting their AI and analytics roadmap\nArchitect and implement a federated Data Mesh across federal program domains, establishing domain ownership and data product standards\nDesign and build modern lakehouse solutions using open table formats (Iceberg, Delta Lake, Hudi) on cloud and on-premise infrastructure\nDefine and enforce data contracts, SLAs, and data-as-a-product standards; develop Data Architecture Decision Records (ADRs) for key platform choices\nImplement data lineage, observability, and quality frameworks meeting federal audit, FISMA, and compliance requirements\nApply privacy-by-design principles throughout the data platform lifecycle; implement data classification, access controls, and sensitive data handling aligned with federal privacy law\nBuild and manage Canonical Data Environments (CDEs) with cross-system reconciliation and master data management\nDevelop data governance artifacts: data dictionaries, lineage maps, quality scorecards, and use-case inventories\nPartner with the AI engineering lead to ensure data platform quality, lineage, and governance supports model training and inference pipelines\nDrive multiple concurrent data workstreams and prioritize ruthlessly across competing client and internal demands\nMentor engineers; codify best practices and publish reusable pipeline templates and governance playbooks\nWhat We're Looking For\n8+ years of data engineering experience with 3+ years in senior or lead architecture roles\nHands-on experience designing and implementing Data Mesh architectures with domain-owned data products\nDeep proficiency in modern lakehouse tooling: Apache Iceberg, Delta Lake, Apache Hudi, or equivalent\nStrong SQL, Python, and at least one orchestration framework (Airflow, Prefect, Dagster)\nExperience with data quality frameworks, metadata management, and data lineage tooling (OpenMetadata, Apache Atlas, or equivalent)\nKnowledge of cloud data platforms: AWS (Glue, Athena, Redshift), Azure (Fabric, Synapse), or GCP (BigQuery, Dataproc)\nUnderstanding of federal data governance, privacy requirements, and data classification frameworks\nUnderstanding of network and cloud architecture including on-premise and hybrid deployments\nProven high-throughput operator — drives multiple concurrent projects and prioritizes ruthlessly\nEffective communicator who translates data architecture decisions to senior federal stakeholders and implementation partners\nBachelor’s degree required; advanced degree preferred\nWe offer remote flexibility, with a preference for candidates local to Maryland.\nBonus Points\nFederal contracting or public sector implementation experience (U.S. federal preferred)\nActive security clearance or ability to obtain one (TS/SCI a significant plus)\nExperience with sensitive data domains: healthcare (HIPAA), defense, or financial data\nFamiliarity with FedRAMP, FISMA, or federal data classification frameworks\nFounding engineer or startup experience — people who have built something from zero\nExperience building or governing master data management (MDM) systems\nCompetencies & What They Look Like at iAdeptive\nCompetency\nWhat It Looks Like at iAdeptive\nTechnical Credibility\nEarns trust by shipping — designs the architecture, implements the first domain, and proves it in production metrics.\nStrategic Thinking\nTranslates federal mission data needs into actionable platform roadmaps and prioritized, funded backlogs.\nData Stewardship\nChampions privacy-by-design, data quality, and governance as first-class engineering concerns — not afterthoughts.\nStakeholder Influence\nCommunicates data architecture trade-offs clearly to engineers, program offices, and federal executives.\nAccountability\nOwns platform decisions end-to-end; maintains ADRs, lineage documentation, and quality scorecards with rigor.\nAdaptability\nTracks the open table format and data mesh ecosystem; adjusts iAdeptive's platform approach before clients ask.\nCollaboration\nPartners with AI engineering, federal clients, systems integrators, and cross-domain data owners to deliver integrated solutions.\nWhy iAdeptive\nFederal 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.\nJob Type: Full-time\nPay: From $130,000.00 per year\nBenefits:\n401(k) matching\nDental insurance\nHealth insurance\nLife insurance\nPaid time off\nProfessional development assistance\nVision insurance\nWork Location: Hybrid remote in Columbia, MD 21046","datePosted":"2026-07-16T17:59:30.686Z","dateModified":"2026-07-16T17:59:30.686Z","hiringOrganization":{"@type":"Organization","name":"Iadeptivetechnologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Columbia","addressRegion":"MD","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"6e42c542f21d6ea23d3b9d68"},"url":"https://jobsearcher.com/jobs/6e42c542f21d6ea23d3b9d68"}}