Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education. For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward. What we offer: Competitive salary Paid vacation/holidays/sick time Comprehensive benefits package including 401K, medical, dental, and vision care On the job/cross training opportunities Encouraging and collaborative team environment Dedication to safety through our Zero Harm policySenior Data Integration Engineer – Workforce AnalyticsRole SummaryWe are seeking a Senior Data Integration Engineer to design, build, and operate scalable data ingestion pipelines that power Workforce Analytics.This role is responsible for acquiring and standardizing data from enterprise systems—especially Workday—into the data platform, using tools such as Fivetran, APIs, and file-based integrations. You will ensure that source data is ingested accurately, reliably, and efficiently to support downstream modeling, analytics, and secure consumption.You will work closely with Data Platform, Data Engineering, and HR systems teams to ensure data is timely, complete, and production-ready.Key ResponsibilitiesData Ingestion & Integration Engineering (Core Focus)Design, build, and maintain scalable ingestion pipelines using:Fivetran (primary tool)REST/SOAP APIsFlat files (SFTP, batch ingestion, vendor extracts)Integrate data from key enterprise systems, including:Workday (core HCM, recruiting, etc.)Other HR, payroll, and workforce-related systemsEnsure ingestion pipelines are robust, efficient, and fault-tolerantWorkday & HR Domain ExpertiseDevelop deep expertise in Workday data structures and integration patternsDesign ingestion strategies for:Worker dataJob/position structuresOrganizational hierarchiesRecruiting and talent dataHandle complexities such as:Effective-dated dataHierarchical relationshipsSlowly changing attributesData Reliability & MonitoringImplement monitoring, alerting, and observability for ingestion pipelinesEnsure data completeness, timeliness, and accuracyTroubleshoot pipeline failures and data discrepancies at the source levelPartner with upstream system owners to resolve data quality issuesFivetran Optimization & ManagementConfigure and optimize Fivetran connectorsManage sync schedules, schema changes, and connector performanceEnsure cost-efficient use of FivetranHandle edge cases where custom ingestion is required beyond FivetranIntegration Design & StandardsDefine best practices for:API-based ingestionFile handling and validationIncremental vs full-load strategiesEstablish standards for naming, metadata, and lineage at ingestion layerEnsure raw data is structured for downstream transformation (Coalesce)CI/CD & Version ControlImplement version control and deployment practices using Azure DevOps / GitHubEnable repeatable, testable deployment of ingestion pipelinesDocument integration logic and configurationsCross-Team CollaborationPartner with:Data Platform Engineering (Snowflake readiness, access patterns)Data Engineers (downstream modeling in Coalesce)HRIS / Workday teams (source system alignment)Ensure clean handoffs between ingestion → transformation → consumptionRequired Qualifications5+ years of experience in data engineering or data integration engineeringStrong experience with Fivetran or similar ingestion toolsExperience integrating data via APIs and flat filesHands-on experience working with Workday integrations or HR data systemsStrong SQL skills and understanding of data structuresExperience building reliable, production-grade data pipelinesFamiliarity with cloud data ecosystems (Snowflake preferred)Preferred QualificationsDeep experience with Workday (HCM, Recruiting, etc.)Experience handling effective-dated and hierarchical datasetsExposure to Workforce / People Analytics domainsFamiliarity with Azure ecosystemExperience with data observability/monitoring toolsUnderstanding of downstream transformation frameworks (Coalesce/dbt)HIRING SALARY RANGE: $100,000-145,000 (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.) This role offers a competitive Bonus plan that will take into account individual, group, and corporate performance. This position includes a competitive benefits package. The posted salary range reflects the target compensation for this role. However, we recognize that exceptional candidates may bring unique skills and experiences that exceed the typical profile. If you believe your background warrants consideration beyond the stated range, we encourage you to apply. To support an efficient and fair hiring process, we may use technology assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. For details, please visit the About Us tab on the Johnson Controls Careers site at https://jobs.johnsoncontrols.com/about-usJohnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability or any other characteristic protected by law. To view more information about your equal opportunity and non-discrimination rights as a candidate, visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.