Data Engineer

• Build and maintain the cloud infrastructure, data pipelines, and deployment workflows
• Calculate measure ratings for the med adherence and avoidance measures
• Collaborate with data scientists, product owners, and business stakeholders
• Deliver scalable, well-architected solutions that move insights from development to production

Senior GCP Data Engineer – Patient Safety Measure Engine

• Lead and grow a team of data engineers, providing mentorship and leadership within the function
• Build the future of the data engineering practice to deliver value to internal and external stakeholders while leveraging cutting edge technologies to dramatically accelerate quality, scale, and depth of delivery
• Design and implement scalable data pipelines to collect, process, and store large volumes of critical data from various sources
• Drive the evolution of the Business Data platform by leveraging modern data technologies like Spark, Airflow, and Databricks
• Collaborate across organizational boundaries with Product, Marketing, and Sales to convert business needs into technical requirements
• Authoritatively translate business use cases into well-thought-out data models that evolve with the business

Director, Data Engineering – Business Data

•The Data Architect will help design, build, and evolve our next‑generation enterprise data platform & data integration pipeline.
•This role is central to our transformation toward a modern, governed, cloud‑based data ecosystem that supports all functions at Coverys (notably underwriting, claims, actuarial, finance, and enterprise analytics etc.).
•The Data Architect will help define the architectural blueprint, establish data modeling standards, and guide the development of scalable, automated data pipelines in Snowflake.
•In addition to design of the architecture, this position will work closely with business and technology teams to ensure data is accurate, trusted, and available for advanced analytics, reporting, and operational decision‑making.
•Design and maintain enterprise data architecture aligned to business domains (Policy, Party, Claims, Billing, Underwriting, etc.).
•Ensure data architecture design aligns to enterprise architecture standards & partners closely with Enterprise Architecture.
•Develop canonical and semantic data models to support analytics, reporting, and operational use cases.
•Define standards for data modeling, data quality, naming conventions, metadata, lineage, and documentation.
•Partner with business stakeholders to translate requirements into scalable data structures.
•Build ELT/ETL pipelines using modern cloud-native tools and frameworks.
•Lead the migration from legacy batch processes to automated, event-driven, or CDC-based ingestion patterns.
•Implement data quality rules, validation frameworks, and reconciliation logic.
•Optimize Snowflake workloads for performance, cost, and reliability.
•Design and oversee medallion-style data layers (bronze/silver/gold) for ingestion, curation, and consumption.
•Work with Data Governance to establish data dictionaries, lineage, classification, data quality and stewardship models.
•Ensure consistent use of canonical identifiers across systems and domains.
•Promote data-as-a-product principles and guide teams toward reusable, scalable data assets.
•Partner with business analysts, data scientists, actuaries, and analytics teams to support data needs.
•Mentor SQL developers and analytics engineers transitioning into modern data engineering roles.
•Mentor and coach the data engineering team & lead the development of pipeline and architecture platforms.
•Provide architectural oversight for major data initiatives across the enterprise.
•Support evolving business needs, as applicable.

Data Architect

• Leads the architecture, engineering, and ongoing operation of the security data lake and associated data products supporting multiple security technologies and data sources
• Establishes the technical roadmap, engineering standards, reusable design patterns, and platform operating model
• Acts as a subject matter expert among peers, with manager and senior management on all matters pertaining to data platforms and the supporting architecture
• Develop and maintain the end-to-end architecture of the security data lake, including ingestion, storage, transformation, enrichment, semantic, and consumption layers
• Ensure data pipelines comply with security policies and regulatory requirements
• Develop testing plans to ensure quality of implementation
• Provide trouble resolution on complex problems and lead implementations for data pipelines, Microsoft Fabric, Azure DevOps, REST API, and source-system integration issues
• Maintain relationship with key vendors
• Create presentations and seek IT management approval and acceptance of significant replacements or reconfigurations of the data pipeline

Senior Data Engineer

• Lead the design, development, and continuous modernization of all CMS sales training curriculum across onboarding, advanced development, and leadership programs
• Architect and deploy scalable digital learning ecosystems, including LMS platforms, virtual delivery models, and AI-driven learning tools
• Integrate artificial intelligence to personalize learning pathways, enhance coaching effectiveness, and drive predictive performance insights
• Develop data platforms and dashboards that connect training initiatives to field execution, adoption, and business performance
• Establish standardized curriculum frameworks grounded in adult learning principles, behavioral change theory, and competency-based development
• Partner with field leadership to identify capability gaps and develop targeted programs to elevate clinical expertise and business acumen
• Lead transformation of existing training content into modern, interactive, and digitally enabled learning experiences
• Drive cross-functional collaboration with Marketing, Sales Operations, and Medical Affairs to ensure alignment with product strategy, clinical evidence, and market dynamics
• Continuously evaluate emerging technologies, AI capabilities, and digital learning trends to keep ZOLL at the forefront of medical device training innovation
• Support and enhance national and regional sales meeting content through innovative curriculum design and delivery strategies
• Elevate clinical acumen across the organization by developing advanced training focused on cardiac physiology, therapy application, and patient pathways
• Strengthen business acumen by building programs focused on territory strategy, account prioritization, and value-based selling
• Enable managers to effectively coach to both clinical and commercial competencies
• Create differentiated learning journeys for new, developing, and tenured representatives to continuously advance performance.

Curriculum Development Manager, Data Platforms

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
• Support both batch and event-driven or CDC-based data workflows
• Improve pipeline reliability, observability, and performance
• Troubleshoot issues in production and proactively solve data quality or system problems
• Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases
• Communicate clearly about implementation choices, tradeoffs, and technical constraints
• Identify opportunities to improve data workflows through better tooling, automation, and engineering practices
• Help shape scalable patterns for how data is ingested, transformed, stored, and accessed

• Pipeline delivery - design, build, and own the Bronze/Silver/Gold lakehouse pipelines that power the NBA platform
• Hands-on development - actively write and ship production SQL, Python, and Spark code alongside your team
• Data modeling - own the Gold layer schema that serves as the canonical member feature set for model training and batch scoring
• Data quality - build and maintain data quality checks, null/sparsity monitoring, and pipeline alerting
• External data integration - onboard new data sources
• Contractor management - manage data engineering contractors within your pod
• Cross-functional partnership - work closely with the Principal Decision Intelligence Engineer on feature requirements

Principal Data Engineer

• The Principal Translational Knowledge Architect & Graph Lead will be responsible for designing and implementing the semantic and knowledge architecture that enables AI-driven reasoning across the drug discovery and development lifecycle.
• This role will serve as the scientific and technical lead for ontology development, knowledge graph design, semantic interoperability, and AI-ready knowledge representation.
• Working at the intersection of translational science, patient safety, biomedical informatics, and artificial intelligence, this individual will help establish the semantic foundation required to connect discovery biology, preclinical safety, clinical development, real-world evidence, and post-marketing safety into a unified reasoning framework.
• The successful candidate will partner closely with scientists, safety experts, data scientists, AI engineers, and platform teams to create knowledge assets that support GraphRAG, agentic AI, scientific reasoning, and next-generation translational intelligence capabilities.

Principal Scientist, Data Science – Translational Knowledge Engineering

• Designing and implementing AI systems to transform raw data into actionable insights
• Developing scalable machine learning models to support client decision-making processes
• Collaborating with cross-functional teams to integrate AI solutions into existing platforms
• Conducting data wrangling and preprocessing to prepare datasets for analysis
• Applying advanced algorithms to enhance the performance of AI models
• Building and deploying software systems that leverage AI and machine learning technologies
• Analyzing complex data sets to identify patterns and trends that inform business strategies
• Supporting client engagements by delivering quality work and adapting to diverse project requirements
• Engaging in continuous learning to deepen technical skills and knowledge in AI engineering
• Upholding professional and technical standards while contributing to team success

AI Engineer, AI Experienced Associate

• Own the technical strategy and roadmap - Own the vision, architecture, and roadmap for the CodaMetrix data platform, ensuring scalability, reliability, regulatory alignment, and operational excellence. Lead key technology decisions, disaster recovery design, architecture reviews, and data engineering standards across teams.
• Platform Engineering at Scale - Design, build, and maintain scalable streaming and batch data platforms Databricks using PySpark, Unity Catalog, Delta Lake, and Structured Streaming. Own Terraform-based infrastructure across environments, including jobs, catalogs, schemas, permissions, compute policies, volumes, and external locations. Build Jenkins CI/CD workflows for automated testing, tagging, and deployments, while optimizing training pipelines, materialized views, retention policies, and production performance.
• Data Governance & Security - Implement and evolve least-privilege access controls across Databricks using Unity Catalog grants, YAML-driven group policies, and schema-level restrictions. Ensure HIPAA and SOC 2 compliance through PHI masking, audit logging, environment-level data segmentation, user provisioning, compute policies, and cost attribution.
• Cost Optimization & Operational Excellence - Drive platform cost reduction through compute policy tuning, serverless optimization, reserved pools, materialized view improvements, and remediation of underutilized resources. Monitor Databricks/AWS spend (using tools like CloudZero and AWS Cost Explorer), own cost attribution and budgeting, resolve production incidents, and maintain runbooks to ensure platform SLAs for uptime and performance.
• Cross-Functional Enablement & Mentorship - Enable ML, BI, Analytics, DevOps, and customer success and implementation teams with training data pipelines, model-ready datasets, feature store architecture, optimized views, dashboards, Tableau refreshes, infrastructure changes, and tenant onboarding. Mentor engineers through code and design reviews, establish quality standards, and serve as a subject matter expert for data platform engineering across the organization.

• Design, develop, and optimize enterprise-scale ETL/ELT data pipelines
• Build scalable data integration solutions for data warehouses and data lakes
• Develop high-performance data processing workflows using Python and SQL
• Design cloud-native data architectures using AWS, Azure, or GCP
• Create and maintain reliable, secure, and scalable data infrastructure
• Implement data governance, security, and quality standards
• Optimize pipeline performance, scalability, and processing costs
• Troubleshoot complex data engineering issues
• Collaborate with business stakeholders to translate requirements into technical solutions
• Mentor junior engineers and promote engineering best practices
• Produce technical documentation for architecture, transformations, and development standards

• Size, architect, and design data protection, disaster recovery, and scale-out storage solutions
• Bring new products and processes to life to meet customer demand
• Serve as the escalation path for L1, L2, and L3 support engineers
• Work directly with customers to solve challenging design and support issues
• Automate the collection of backup system health, backup and recovery jobs, and general environment status
• Monitor backup systems and performance, identify issues needing attention

Data Protection Engineer

• Lead a team of 2-3 engineers
• Working with fellow Nava engineers to design, review, and build well-crafted software
• Working in an agile manner to efficiently ship new features that meet user needs
• Design and develop scalable data ingestion and processing pipelines
• Implement large-scale data ecosystems within cloud-based platforms that include data management and data governance of structured and unstructured data
• Implement data validation and quality checks to ensure accuracy and consistency
• Work with cross-functional project teams to gather business requirements and translate to detailed technical specifications
• Work with Government partners to assist and develop data engineering applications and pipelines that will enable data services and processing capabilities
• Participate in software design and code reviews
• Maintain security and privacy standards in all aspects of the data pipeline
• Taking part in hiring activities (e.g., submitting referrals, conducting interviews, and attending interview debriefs), as needed

Senior Software Engineer, Data

• Become a healthcare insurance subject matter expert with sufficient technical skills to produce proof-of-concept solutions to various issues within the industry.
• Perform data cleaning and analysis using SQL, Python, and AI models.
• Analyze big data from diverse sources to identify trends, address gaps, and discover improvement opportunities that align with improving the healthcare system.
• Provide subject matter expertise in identifying product uses and designing strategies that address significant business and technical challenges.
• Gather and translate business requirements into analytical applications and advanced dashboard visuals, reports, or other alert systems.
• Document code using documentation tools and participate in collaborative team code reviews.
• Collaborate with various teams within the company to advise on technical solutions.
• Stay informed on industry trends, best practices, and innovations, ensuring competitive market relevance of company products.

Senior Business Data Engineer

• Build and optimize analytical data models in BigQuery.
• Implement partitioning, clustering, and materialized views for performance and cost efficiency.
• Ensure compliance with data governance, access controls, and IAM best practices.
• Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches.
• Utilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic.
• Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows.
• Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability.

• Design and implement the canonical data model for Vultr’s control plane ERP transformation: product catalog, chart of accounts, financial transactions, cost centers
• Build and maintain the internal APIs and event streams that Finance, Analytics, and downstream systems consume
• Refactor existing administer code toward clean domain boundaries (no more conflated orders/ledger/report tables)
• Implement data upgrade/migration paths from legacy schemas without breaking production
• Write the integration layer between administer and Vultr's existing billing, provisioning, and reporting systems
• Establish data validation and integrity checks across the financial data layer
• Collaborate with the Product Manager to translate finance domain requirements into durable schema designs
• Document architectural decisions and data model contracts for downstream consumers

Senior Software Engineer, ERP, Data & Domain

• Manage and maintain all software and hardware for Gas SCADA and Remote Terminal Unit (RTUs)
• Implement and design RTU programming to support field projects
• Troubleshoot the SCADA system for uninterrupted operations
• Evaluate and integrate latest gas monitoring equipment and telecommunication options
• Support all company capital projects in SCADA until fully commissioned

IT Data Engineer IV

• lead a team of data architects in the Asset Management Technology’s architecture team
• set the architectural direction for AI-ready platforms
• establish governance frameworks that enable consistent excellence
• build and develop high-performing data architecture teams
• architect and deliver high-impact solutions
• design and optimize enterprise-scale data platforms
• establish reference architectures and accelerators
• lead technical deep dives and design reviews

Vice President, Data Architecture

• Own the building, maintenance, and optimization of pipelines to ingest data from both operational databases and third-party tools into a data lake/warehouse.
• Architect highly efficient ingestion patterns that handle evolving data schemas and high-volume, multi-source data streams seamlessly.
• Optimize pipeline performance to ensure maximum uptime, high throughput, and cost-effective compute usage.
• Use dbt to transform raw data within the data warehouse into structured, production-ready schemas.
• Write templated SQL and Jinja code to enforce macro-driven, modular, and DRY (Don't Repeat Yourself) development practices.
• Perform rigorous data quality checks by implementing native dbt tests.
• Set up monitoring and alerting frameworks around both ingestion routines and dbt builds.
• Track pipeline health metrics to measure and report on overall data freshness and platform reliability.
• Build data applications that interact with the data warehouse to empower decentralized self-service analytics.
• Build internal tooling and libraries to facilitate analytics and ML work.

Staff Data Engineer

• Lead the roadmap, sustainment, and modernization strategy for D360 and RIF.
• Ensure these platforms continue to meet critical business needs across discovery and preclinical research.
• Lead a cross-functional team responsible for platform delivery, support, data operations, and engineering coordination.
• Oversee delivery across internal teams and external partners supporting sustainment and transformation work.
• Partner across the Molecules & Assays Solutions portfolio along with key business stakeholders across Research Units and Partner Lines.
• Drive accountability for data quality, lineage, usability, and trust across scientific data flows.
• Work closely with scientific users, product leaders, business analysts, and technical teams to prioritize the highest-value improvements.

Data Engineer jobs in Massachusetts

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Senior GCP Data Engineer – Patient Safety Measure Engine

Director, Data Engineering – Business Data

Data Architect

Senior Data Engineer

Curriculum Development Manager, Data Platforms

Senior Data Engineer

Principal Data Engineer

Principal Scientist, Data Science – Translational Knowledge Engineering

AI Engineer, AI Experienced Associate

Principal Data Engineer

Senior Data Engineer

Data Protection Engineer

Senior Software Engineer, Data

Senior Business Data Engineer

Data Engineer

Senior Software Engineer, ERP, Data & Domain

IT Data Engineer IV

Vice President, Data Architecture

Staff Data Engineer

Director, Scientific Data Platforms Lead