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About the Role
This role will evolve GATX’s data platform into a scalable, self-service data and AI ecosystem, reporting to the Director, Analytics Engineering & Integration within the Data, Analytics, Reporting and Integration group.
Responsibilities
- Support new development requests, enhancements, and project initiatives that deliver data integration solutions aligned with business requirements.
- Collaborate with project teams, senior data engineers, architecture, infrastructure, analytics teams, business stakeholders, and external partners to support Data Mart, Data Warehouse, and cloud-based analytics platform needs.
- Participate in all phases of the Software Development Life Cycle (SDLC) for data integration, ETL, and cloud-based data pipeline development.
- Assist in designing, developing, testing, deploying, and supporting batch and near-real-time data pipelines on AWS and Databricks.
- Develop data transformations using SQL, Python, Spark, Delta Lake, and established data engineering patterns.
- Develop and maintain Databricks notebooks, workflows, jobs, Delta tables, and related data components.
- Follow established architecture, coding, DevOps, security, governance, and documentation standards.
- Create unit tests and assist with integration, reconciliation, performance, and regression testing.
- Investigate data quality, pipeline, and production-processing issues, escalating complex problems when appropriate.
- Create and maintain source-to-target mappings, transformation rules, data flow diagrams, and operational documentation.
- Build an understanding of supported business processes, source systems, reporting requirements, and upstream and downstream dependencies.
- Participate in platform upgrades, deployment automation, monitoring improvements, and operational process enhancements.
- Continuously develop expertise in AWS, Databricks, Spark, Python, SQL, Delta Lake, Unity Catalog, and modern data engineering practices.
- Assist in monitoring the health, performance, and reliability of data pipelines, ETL processes, and cloud-based data platform components.
- Support established monitoring, alerting, and operational procedures to help ensure data processing service levels and platform availability are maintained.
- Monitor daily production processes and work with IT administrators, support teams, and other DARI team members to investigate, troubleshoot, and resolve production issues.
- Maintain an understanding of established service level agreements (SLAs) and provide support that meets operational and business expectations.
- Participate in continuous improvement initiatives focused on reducing production incidents, improving system stability, and enhancing the overall customer experience.
- Diagnose and resolve data integration, ETL, and pipeline issues with guidance from senior team members, escalating complex issues as appropriate.
- Support the timely resolution of business-impacting data integration defects, failures, and processing issues to minimize disruptions to downstream reporting and analytics.
- Assist in root cause analysis activities and contribute to the implementation of corrective and preventive actions to improve platform reliability and operational efficiency.
- Create and maintain operational documentation, troubleshooting guides, and knowledge base articles to support ongoing platform operations and team knowledge sharing.
- Participate in a scheduled on-call rotation.
- Stay informed about emerging data engineering technologies, cloud platform capabilities, and new releases of tools used by the Analytics and Data Integration teams.
- Assist in evaluating new features, enhancements, and upgrades to data integration and analytics platforms, providing input on potential improvements and implementation opportunities.
- Support the administration, configuration, testing, and maintenance of data integration tools and cloud-based data platform solutions.
- Participate in the implementation, testing, and rollout of platform upgrades, patches, and new capabilities.
- Apply and promote established development, data engineering, security, and operational best practices to support reliable, scalable, and maintainable solutions.
- Collaborate with senior engineers and team members to identify process improvements, automation opportunities, and operational efficiencies.
- Continuously expand technical knowledge and skills through training, self-development, and hands-on experience with modern data engineering tools, frameworks, and cloud technologies.
Requirements
- Bachelor’s degree in a quantitative or technical discipline such as Information Technology, Computer Science, Statistics, Economics, Mathematics, Engineering, or a related field.
- 1-3 years of experience in software development, data engineering, ETL development, data integration, analytics, or a related technical discipline within large, multi-platform enterprise environments (Windows, Unix, Oracle).
- Exposure to or experience with data integration, ETL processes, data warehousing, or cloud-based data platforms.
- Familiarity with Databricks, Apache Spark, Delta Lake, or similar big data technologies is preferred.
- Basic understanding of cloud platforms, preferably AWS, including services such as Amazon S3, IAM, and cloud-native data storage concepts.
- Experience working with SQL and relational databases for data extraction, transformation, and analysis.
- Basic programming experience in Python, SQL, or similar languages used for data engineering and analytics solutions.
- Understanding of data warehousing concepts, data modeling fundamentals, and data integration best practices.
- Familiarity with software development lifecycle (SDLC) processes and Agile development methodologies; experience with Jira or similar project management tools is a plus.
- Strong analytical, problem-solving, and troubleshooting skills with the ability to learn new technologies quickly.
- Ability to work effectively in a collaborative team environment and communicate technical concepts to both technical and non-technical stakeholders.
- Demonstrated attention to detail and commitment to delivering high-quality, reliable solutions.
- Working knowledge of Unix shell scripting is a plus.
- Asset leasing industry experience is a plus, particularly within the Rail sector.
- Relevant certifications (e.g., Databricks Certified Data Engineer, AWS Certified Data Analytics, Azure Data Engineer) are preferred.
- Occasional travel may be expected.
- Occasional work on nights and weekends to support production environment and meet project demands and deadlines.
Skills
- Apache Spark (PySpark preferred)
- Python
- SQL
- Relational databases
- PL/SQL
- Database concepts
- Data structures
- Data mapping
- Data transformations
- Data modeling principles
- Databricks
- Delta Lake
- Databricks Workflows and Jobs
- Data ingestion pipelines
- Data transformation pipelines
- Batch data processing
- Incremental data loading
- Change Data Capture (CDC) concepts
- Streaming data fundamentals
- Medallion Architecture (Bronze, Silver, Gold)
- Batch data processing concepts
- Streaming data processing concepts
- Data product design concepts
- Domain-oriented design concepts
- Dimensional data modeling
- Data quality principles
- Data governance principles
- Data lifecycle management
- Modern data platform concepts
- Data lakes
- Data warehouses
- Lakehouse architecture
- Enterprise data architecture patterns
- Git-based version control systems
- CI/CD concepts
- Automated deployment practices
- Development environment management
- Test environment management
- Production environment management
- Source control
- Code reviews
- Testing
- Deployment processes
- Data pipeline testing
- Data quality validation
- Data security
- Access controls
- Data governance practices
- Databricks Unity Catalog
- Cloud cost management
- Performance monitoring
- Optimization concepts
- Data lineage
- Compliance requirements
- Data visualization concepts
- Microsoft Office Suite (Word, Excel, PowerPoint)
- Enterprise data platform integration
- Lakehouse platform integration
- Transactional system integrations
Location
- Chicago, IL
- Remote
Work Type
- Remote
- Hybrid
Experience Level
- 1-3 years
Education Level
- Bachelor’s degree in a quantitative or technical discipline
Salary/Compensations
- USD $80,800.00/Yr. - USD $96,000.00/Yr.
Benefits
- Short-term incentive plan
About the Company
- Founded in 1898 and headquartered in Chicago, IL, GATX Corporation (NYSE: GATX) is an industry leader with 125+ years of success.
- Proud of its high-performance culture, hard-working and enthusiastic management team, and beautiful office space in the Willis Tower.
- GATX hires the best and offers employees a dynamic, energetic, collaborative environment to enable them to make an impact from day one.
- Enjoy the perks and benefits of a global company with the close-knit culture and community of a much smaller one.
- Dedicated to providing people with the tools and resources they need to advance in their careers.