{"id":3893765,"url":"https://alion.io/job/nextech-senior-data-engineer","title":"Senior Data Engineer","company":{"id":679956,"name":"Nextech","domain":"nextech.com","url":"https://alion.io/company/nextech-2","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"C","score":58,"open_postings":3,"ghost_share":0.333,"stale_share":0.667,"repost_share":0.333,"time_to_fill_p50_days":36,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"HIPAA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Bicep","optional":true},{"name":"FHIR","optional":true},{"name":"HL7","optional":true},{"name":"MS SQL","optional":true},{"name":"PowerShell","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-11-06T21:49:21Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-06T22:25:24Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Summary\nThe Senior Data Engineer will be part of a six-person Data Services team supporting mission-critical healthcare applications, including real-time clinical workflows, patient data analytics, and regulatory reporting. The team has deep SQL Server expertise, and this position represents an intentional step toward expanding its capabilities in modern data engineering, lakehouse architecture, and agentic AI.\nThis individual will help build and enhance the enterprise lakehouse, curate the semantic layer needed to make AI-driven analytics reliable, and partner closely with Product Engineering, FP&A, and other teams that depend on accurate and accessible data. During the first year, the Senior Data Engineer is expected to drive meaningful technical debt reduction within the enterprise lakehouse, become a trusted technical partner across product roadmaps, and strengthen the capabilities of junior engineers through active mentorship.\nThis role is well suited for a data engineer who is energized by the intersection of lakehouse architecture and emerging agentic AI patterns and wants to develop these capabilities within a healthcare environment where data quality has meaningful consequences.\nAll activities must be in compliance with Equal Employment Opportunity laws, HIPAA, ERISA, and other regulations, as appropriate.\nEssential Functions:\nIn addition to working in accordance with appropriate conduct and behavioral standards, specific responsibilities of this role include:\nDesign and build robust data pipelines and lakehouse solutions using Databricks, Microsoft Fabric, PySpark, and Python. \nDesign AI-ready schemas, semantic layers, and metadata structures that allow AI agents to query data accurately and reliably. \nBuild automated validation processes for agent-generated queries. \nPilot agentic automation for data quality and reconciliation workflows while measuring accuracy and maintaining clear rollback plans. \nCurate and maintain the semantic layer that grounds AI agents and reduces incorrect responses caused by ambiguous or poorly defined data. \nCatalog and steward enterprise data assets to support internal analytics, financial planning, and product engineering needs. \nPartner proactively with Product Engineering, FP&A, and other stakeholders to identify and understand data requirements. \nTroubleshoot performance issues and support SQL Server and Azure SQL environments while continuing to develop operational expertise. \nMentor junior engineers on data engineering best practices, architecture patterns, and technical standards. \nContribute to data protection, security, and compliance reviews to ensure that tools and processes meet applicable standards, including HIPAA requirements where relevant. \nCarry out additional responsibilities assigned based on business needs. \nMinimum Requirements:\n7+ years of production experience in data engineering roles, including hands-on experience building and maintaining data pipelines at scale. \nAdvanced proficiency with Python and PySpark or Apache Spark in production data engineering environments. \nHands-on production experience with Databricks, Microsoft Fabric, or comparable modern data platforms. \nDemonstrated experience designing, implementing, and operating lakehouse architectures using Delta Lake, Parquet, or equivalent technologies. \nExperience designing AI-ready schemas, semantic layers, or metadata structures with downstream AI or machine learning query patterns in mind, or experience building automated validation for programmatically generated queries. \nExperience with agentic or automation-driven data quality workflows, such as AI-assisted reconciliation, agent-grounded semantic layers, or comparable applied solutions. \nDemonstrated ability to partner directly with product, analytics, finance, or business stakeholders to understand and shape data requirements proactively. \nFamiliarity with Microsoft Azure cloud concepts, including platform as a service, infrastructure as a service, Azure SQL, and hybrid cloud models. \nWillingness and ability to develop deeper operational expertise within Azure SQL and SQL Server environments. \nMeaningful experience mentoring junior or mid-level engineers on technical standards, architecture patterns, and data engineering best practices.\nPreferred Qualifications:\nHands-on production experience with Azure SQL, SQL Server, or Azure SQL Managed Instance. \nProficiency with T-SQL and PowerShell for automation and operational support. \nExperience with infrastructure-as-code tools such as Terraform, Bicep, or Azure Resource Manager templates. \nFamiliarity with streaming data architectures and technologies such as Azure Event Hubs or Apache Kafka. \nUnderstanding of data mesh principles and distributed data ownership. \nExperience working within healthcare or another regulated industry. \nFamiliarity with HIPAA requirements or healthcare data standards such as FHIR and HL7.\nWorking Environment/Physical Demands:\n 100% Remote in the United States\nActivities require a significant amount of work in front of a computer monitor\nLong-distance or air travel as needed - 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