Data Engineer

At BioAgilytix, we are passionate about premier science and the impact it has on our world. Our team of highly experienced scientists and professionals deliver tailored services for supporting new medicine breakthroughs with best-in-class bioanalytical services. We are tirelessly committed to our customers by being solution-oriented and deadline-driven. . . and we are growing. Our culture is fast-paced, fun and never boring. Because we work across numerous clients and drug modalities, your career can develop rapidly. You’ll gain experience with a variety of challenges all while you enable life-changing, life-saving therapeutics to the patients who need them. The Data Engineer is a hands-on technical lead responsible for designing, building, and supporting BioAgilytix's Enterprise Data Platform. This role develops scalable, validated, production-ready data pipelines, enterprise data models, and certified data products supporting laboratory operations, scientific analytics, sponsor reporting, regulatory compliance, and AI initiatives. Working under the direction of the Data Management Lead, and collaborating with cross-functional stakeholders, this role implements modern data engineering practices including Snowflake, dbt, dimensional modeling, semantic modeling, CI/CD automation, DataOps and enterprise data governance standards. Essential Responsibilities Design, develop, and support scalable enterprise data platforms that enable trusted, governed, and high-quality data products for analytics, scientific operations, sponsor reporting, regulatory compliance, and AI initiativesBuild and maintain production-grade ELT pipelines that integrate data from laboratory information systems (LIMS), ERP, CRM, APIs, sponsor systems, cloud applications, and other enterprise data sourcesDevelop modular, reusable data transformation frameworks using modern ELT practices, including automated testing, documentation, lineage, version control, and deployment automationDevelop and implement dimensional data models, semantic models and governed datasets based on the established enterprise business definitions across the organizationDevelop validated, traceable, and auditable data pipelines supporting regulated laboratory operations, sponsor deliverables, and enterprise reporting while ensuring data integrity, reproducibility, lineage, and compliance with GxP, GLP, HIPAA, 21 CFR Part 11, and enterprise data governance standardsImplement automated data validation, reconciliation, data quality controls, audit logging, monitoring, observability, and operational alerting to ensure reliable and trusted enterprise dataOptimize the performance, scalability, security, governance, and operational efficiency of the enterprise data platformProvide operational support for the enterprise data platform through production monitoring, incident resolution, root cause analysis, and continuous reliability improvementsSupport sponsor-facing data delivery by building automated data harmonization, transformation, validation, lineage, and regulatory reporting processesDevelop certified, governed, and AI-ready data products that support enterprise analytics, machine learning, semantic search, and generative AI initiativesCollaborate with Laboratory Operations, Quality teams, Information Technology, and business stakeholders to deliver scalable, reusable, and governed enterprise data solutions Additional Responsibilities Other duties as needed Minimum Preferred Qualifications: Education/Experience Bachelor’s degree in computer science, Information Systems, Engineering, Mathematics, Data Science, or related field; Master's preferred5+ years of experience in Data Engineering, Data Management, Software Engineering, Business Intelligence, or related technical disciplines, preferably within life sciences, biotechnology, pharmaceuticals, CROs, healthcare, or other regulated industries3+ years of hands-on experience designing, developing, and supporting enterprise-scale data engineering solutions in production environments3+ years of hands-on experience architecting, developing, and administering enterprise solutions using Snowflake as a primary cloud data platform, including performance optimization, security, governance, workload management, and operational support Minimum Preferred Qualifications: Skills Strong hands-on experience with dbt Cloud or dbt Core for modular data transformation, automated testing, documentation, lineage, and deploymentDemonstrated expertise in enterprise dimensional data modeling, including star schemas, conformed dimensions, slowly changing dimensions, snapshot fact tables, and analytical data warehouse designExperience designing semantic models, enterprise business vocabularies, ontology-driven data products, or knowledge graph concepts that enable consistent business definitions across enterprise analyticsStrong proficiency in SQL and Python for enterprise data engineering, automation, data transformation, and performance optimizationExperience developing enterprise data integration solutions using ETL/ELT platforms such as Talend, Fivetran, or equivalent technologiesExperience integrating enterprise applications using REST APIs, GraphQL APIs, file-based interfaces, Change Data Capture (CDC), and event-driven messaging platformsExperience with a cloud platform including AWS (S3, Lambda, ECS, Glue) and/or AzureExperience designing, developing, validating, and maintaining certified enterprise data products with documented business definitions, transformation logic, lineage, ownership, and lifecycle managementExperience implementing least-privilege security, role-based access control (RBAC), data masking, row-level security, encryption, secrets management, and secure data sharingExperience supporting enterprise production data platforms, including incident management, root cause analysis, operational monitoring, performance tuning, release management, and platform reliability engineeringExperience working with Laboratory Information Management Systems, bioanalytical data, sponsor deliverables, and regulated laboratory environments is strongly preferredExpert proficiency in SQL and PythonSnowflake architecture including Snowpark, Dynamic Tables, Streams, Tasks, data sharing, security, governance, workload management, and performance tuningdbt Cloud/Core including models, snapshots, macros, tests, semantic models, documentation, lineage, and deployment automationEnterprise ETL/ELT frameworks including Fivetran/Talend, APIs, CDC, and event-driven integrationsEnterprise data architecture, metadata-driven architecture, medallion architecture, and modern cloud data platform design patternsGit, GitHub Actions, CI/CD, Infrastructure-as-Code, and DataOps practicesAutomated testing, observability, reconciliation, data quality, lineage, and operational monitoringPower BI, Sigma, Tableau, and semantic reporting platformsAbility to independently deliver assigned complex data engineering solutions within established architecture, priorities, procedures, and technical standardsAbility to translate complex scientific, laboratory, and business requirements into scalable enterprise data models, semantic models, and certified data products based on established architectural and business standardsStrong analytical, troubleshooting, and optimization skills. Applies comprehensive data engineering knowledge and advanced analytical techniques to investigate complex issues, identify root causes, evaluate available information, and recommend appropriate solutionsAbility to develop validated, traceable, and auditable data solutions in accordance with established compliance, validation, quality, and scientific data-integrity requirementsCollaborate effectively across Scientific Operations, Quality Engineering, Quality Assurance, and IT, with the ability to communicate clearly with stakeholders at all levels of the organizationDemonstrated ability to work independently on complex data engineering assignments, use professional judgment to adapt established approaches, and escalate decisions affecting enterprise architecture, governance strategy, security policy, compliance strategy, or platform directionExcellent communication and documentation skillsAble to navigate a fast-paced, evolving data landscape, demonstrating resilience and flexibility in the face of new challengesExcellent written and spoken English language skillsExcellent interpersonal and negotiating skillsStrong presentation skillsExcellent computer skills Preferred Credentials Master’s degree Supervisory Responsibility: No supervisory responsibilities Supervision Received Reports to the Data Management Lead and works independently on complex engineering initiatives Infrequent supervision and instructionsFrequently exercises discretionary authority Physical Demands Ability to work in an upright and/or stationary position for up to eight (8) hours per dayRepetitive hand movement of both hands with the ability to make fast, simple, repeated movements of the fingers, hands, and wrists to operate office equipmentOccasional mobility neededOccasional crouching, stooping, with frequent bending and twisting of upper body and neckLight to moderate lifting and carrying (or otherwise moving) objects, including luggage and laptop computer, with a maximum lift of 20 poundsAbility to access and use a variety of computer software Ability to communicate information and ideas so others will understand, with the ability to listen to and understand information and ideas presented through spoken words and sentencesFrequently interacts with others to obtain or relate information to diverse groupsWorks independently with little guidance or reliance on oral or written instructions and plans work schedules to meet goals; requires multiple periods of intense concentrationPerforms a wide range of variable tasks as dictated by variable demands and changing conditions with little predictability as to the occurrenceAbility to perform under stress and multi-taskRegular and consistent attendance Position Type and Expected Hours of Work This is a full-time positionSome flexibility in hours is allowed, but the employee must be available during the “core” work hours as published in the BioAgilytix Employee HandbookOccasional weekend, holiday, and evening work needed Benefits And Other Perks Medical Insurance (HDHP with HSA; PPO), Dental Insurance, Vision Insurance, Flexible Spending Account (medical; dependent care), Short Term Disability | Long Term Disability Life Insurance, Paid Time Off (4 weeks per year), Parental Leave, Paid Holidays (9 scheduled; 5 floating), 401k with Employer Match, Employee Referral Program COMMITMENT TO EQUAL OPPORTUNITY BioAgilytix provides equal employment opportunities to all employees and applicants for employment without regard to race, color, ancestry, national origin, gender, sexual orientation, marital status, religion, age, disability, gender identity, results of genetic testing, service in the military, or any other group protected by federal, state, or local law. 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