Engineer the applications, automations, integrations, and AI-powered experiences that transform manual HR processes into modern digital services.
Compensation
$105,786 - $141,047 in these states: AL AR AZ FL GA IA ID IN KS KY LA ME MO MS MT ND NE NM OH OK PA SC SD TN UT VT WI WV WY
$111,074 - $148,099 in these states: CO HI MI MN NC NH NV OR RI
$116,364 - $155,152 in these states: AK CA CT DC DE IL MA MD NJ NY TX VA WA
Responsibilities
Design, build and support end-to-end automated workflows in Power Automate
Build and maintain robotic process automations for systems lacking modern integration capabilities
Implement logging, alerting, retry mechanisms, and operational monitoring
Identify opportunities to eliminate manual effort while balancing automation benefits
Develop Power Apps solutions and custom applications
Requirements
Bachelor's degree in Computer Science, Information Systems, Engineering, Data Analytics, HRIS, or a related field
Senior Business Intelligence Analyst II responsible for design, development, governance, deployment, and support of complex business intelligence and reporting solutions.
Locations (2)
Center Valley, Pennsylvania, United States
Westborough, Massachusetts, United States
Compensation
The anticipated base pay range for this full-time position in this location is $94,580.00 - $132,412.00 / year, plus potential for annual bonus (subject to plan eligibility and other requirements).
Responsibilities
Own development and delivery of assigned business intelligence and reporting solutions
Serve as primary technical reporting owner for Corporate Accounts
Partner with business leaders and cross-functional teams to understand reporting needs
Design, develop, optimize, and maintain advanced Power BI reports and dashboards
Partner with Data Engineering, IT, and Data and Analytics teams to define reporting requirements
The Senior Manager is a capability leader within Data Engineering & Semantics, owning one or more capability areas — such as Data Engineering, Data Product Management or Data Trust & Reliability Engineering — while retaining sufficient breadth to lead across the team mandate and complex CEI PODs. The role turns DSM-led business requirements into trusted, governed and AI-ready data, including the CL layer of the AI Empowered Consumption Layer (AICL), so that reporting, analytics and AI solutions work from one consistent data foundation.
Responsibilities
Own one or more team capability areas end to end, defining capability roadmaps, engineering standards, reusable patterns, controls, service expectations and lifecycle outcomes across China CEI
Lead and govern Data Engineering across L1–L4 — ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations
Lead technical management and lifecycle governance of BI platforms, including workspace and environment administration, access controls, release management, refresh reliability, performance, capacity and license utilization
Lead and govern Data Product Management — reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer (AICL) and agent-facing data contracts
Lead and govern Technical Semantics — semantic models, metadata, taxonomies and technical mappings that implement DSM-approved business definitions and harmonized KPIs
Requirements
Bachelor’s degree or above in Computer Science, Data Engineering, Data Science, Information Systems or a related computing discipline
The Senior Manager is a capability leader within Data Engineering & Semantics, owning one or more capability areas — such as Data Engineering, Data Product Management or Data Trust & Reliability Engineering — while retaining sufficient breadth to lead across the team mandate and complex CEI PODs. The role turns DSM-led business requirements into trusted, governed and AI-ready data, including the CL layer of the AI Empowered Consumption Layer (AICL), so that reporting, analytics and AI solutions work from one consistent data foundation.
Responsibilities
Own one or more team capability areas end to end, defining capability roadmaps, engineering standards, reusable patterns, controls, service expectations and lifecycle outcomes across China CEI.
Lead and govern Data Engineering across L1–L4 — ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations.
Lead technical management and lifecycle governance of BI platforms, including workspace and environment administration, access controls, release management, refresh reliability, performance, capacity and license utilization; partner with Enterprise Engineering for production operations and implement GCA DSM-approved business definitions and KPIs.
Lead and govern Data Product Management — reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer (AICL) and agent-facing data contracts.
Lead and govern Technical Semantics — semantic models, metadata, taxonomies and technical mappings that implement DSM-approved business definitions and harmonized KPIs.
Senior Manager is a capability leader within Data Engineering & Semantics, owning one or more capability areas and leading across the team mandate and complex CEI PODs.
Responsibilities
Own one or more team capability areas end to end, defining capability roadmaps, engineering standards, reusable patterns, controls, service expectations and lifecycle outcomes across China CEI
Lead and govern Data Engineering across L1–L4 — ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations
Lead technical management and lifecycle governance of BI platforms, including workspace and environment administration, access controls, release management, refresh reliability, performance, capacity and license utilization
Partner with Enterprise Engineering for production operations and implement GCA DSM-approved business definitions and KPIs
Lead and govern Data Product Management, Technical Semantics and Data Trust & Reliability Engineering
Requirements
Bachelor’s degree or above in Computer Science, Data Engineering, Data Science, Information Systems or a related computing discipline
The Manager is a delivery owner within Data Engineering & Semantics, and may be assigned to a specific capability or deployed into a cross-functional CEI POD based on portfolio priorities. The role combines hands-on data engineering, data product and data quality delivery with backlog, quality, readiness and stakeholder accountability, including delivery of the AICL CL layer.
Responsibilities
Manage day-to-day delivery for assigned data engineering, data product, semantic or data-quality outcomes.
Own day-to-day delivery of Data Engineering across L1–L4 — ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations.
Own day-to-day delivery of reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer (AICL) and agent-facing data contracts.
Own day-to-day delivery of technical semantics — semantic models, metadata, taxonomies and technical mappings that implement DSM-approved business definitions and harmonized KPIs.
Own day-to-day delivery of Data Trust & Reliability Engineering — technical data governance controls, shift-left data quality checks, lineage, observability and China data, privacy and cross-border controls.
Requirements
Bachelor’s degree or above in Computer Science, Data Engineering, Data Science, Information Systems or a related computing discipline
Lead design and development of scalable Power BI dashboards, semantic models, and reporting solutions, driving performance optimization and providing technical leadership.
Responsibilities
Lead design and development of scalable Power BI dashboards, semantic models, and reporting solutions
Drive performance optimization across reports, DAX calculations, data models, and refresh processes
Design efficient data models integrating Power BI with Snowflake and other enterprise data sources
Troubleshoot reporting, performance, refresh, and upstream data-quality issues
Provide technical leadership, architecture guidance, code/design reviews, and development standards for the Power BI team
Requirements
Bachelor's in Computer Science or equivalent work experience
Nice to have: Finance or Financial Services reporting
Lead a team of developers responsible for designing, developing, deploying, and supporting enterprise reporting and business intelligence solutions using Power BI, SQL Server Reporting Services (SSRS), and SQL.
Responsibilities
Develop, troubleshoot, and support SQL Server Reporting Services (SSRS) and Power BI solutions
Build and optimize SQL, DAX, and Power Query solutions, including complex queries, and stored procedures
Assemble datasets and semantic models from SQL Server and Snowflake data warehouses
Keep Git source code repositories and product documentation updated and accurate
Conduct solution architecture reviews and code reviews
Requirements
Bachelor's degree in Computer Science, Information Systems, Business Intelligence, Data Analytics, or a related field
Lead persona-driven discovery and design for automation opportunities across the Data & Analytics organization, starting with data quality, recurring reporting, and audience management.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Establish and operate metadata, semantic, and data quality capabilities that enable governed, high-quality data assets.
Partner with automation teams to scale controls and automations that improve data quality, access management, and compliance outcomes.
Conduct structured discovery with targeted analyst personas to identify high-frequency workflows suited for automation.
Define problem statements, success criteria, and measurable outcomes for pilots and product releases.
Design and run inclusive, hands-on testing programs to gather real-world feedback from diverse analyst groups.
Requirements
Nice to have: enterprise-scale data quality programs
Bachelor’s degree in Data Analytics, Business Intelligence, Information Systems, Computer Science, Statistics, Mathematics, Business, Finance, or a related field
Master’s degree in a related field
Nice to have: Experience in healthcare, medical devices, life sciences, sales operations, commercial analytics
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