Responsibilities
- Modernize and expand the L&D data infrastructure to support new KPIs, logistics process visibility, and business growth.
- Migrate legacy ETL pipelines and filesystem logic into corporate-approved, scalable cloud technologies and operational standards.
- Convert the current file-based logistics data repository into a Snowflake environment aligned with enterprise architecture and governance.
- Design and maintain automated, reliable data ingestion pipelines integrating transportation, warehouse, carrier, audit, and regional operational data sources.
- Build foundational data models that support logistics analytics and downstream Power BI dashboards.
- Integrate logistics datasets with JCI’s corporate data lake, ensuring proper mapping, lineage tracing, and compliance with central architecture.
- Establish data dictionaries, documentation, and standard processes for logistics KPIs where none currently exist.
- Implement data quality monitoring to detect anomalies in shipments, orders, events, carrier performance, throughput, etc.
- Collaborate with regional logistics teams, business partners, and technical groups to ensure data accuracy and consistent interpretation across all operational metrics.
- Ensure alignment with corporate data security, compliance, and retention requirements.
- Support predictive analytics initiatives such as ETA modeling, exception forecasting, and demand prediction through well-structured data pipelines.
- Participate in ad-hoc logistics and distribution data engineering projects as needed.
Requirements
- Bachelor’s degree in Data Engineering, Computer Science, Data Analytics, Information Systems, or related field.
- 4+ years of experience in data engineering, BI engineering, or data architecture roles.
- Experience supporting supply chain, logistics, transportation, or distribution data systems.
- Strong SQL expertise and hands-on experience with ETL/ELT tools and cloud data platforms.
- Hands-on experience designing, orchestrating, and maintaining pipelines using Azure Data Factory (ADF).
- Experience working with Snowflake or other modern cloud data warehouses.
- Ability to integrate, clean, and model fragmented datasets from TMS, WMS, ERP, carrier systems, audit platforms, etc.
- Understanding of data governance, quality frameworks, and metadata documentation.
- Experience building data models for BI tools like Power BI.
- Ability to translate operational logistics requirements into technical solutions.
- Strong communication and collaboration skills.
- Conversational English.
Nice to Have
- Experience with enterprise-scale data lakes (Azure Data Lake, AWS S3).
- Knowledge of Python, Spark, dbt, or similar transformation frameworks.
- Experience enabling predictive analytics or machine learning pipelines.
- Familiarity with logistics metrics (OTD, SLA, cost-to-serve, dwell time, throughput).
- Experience in environments where processes and data sources are still being standardized.
Benefits
- Comprehensive benefits package.
- Opportunities for professional growth and development.
- Supportive and inclusive work environment.
- Commitment to work-life balance and employee well-being.
- Engagement in meaningful projects that make a difference.
Additional Information
- Conversational English.
- Johnson Controls does not request pregnancy or HIV testing as a condition for hiring, continued employment, or promotion, in accordance with its commitment to labor equality and non-discrimination.
