Job Summary:
Leads projects for the design, development, and maintenance of a data and analytics platform. Effectively and efficiently processes, stores, and makes data available to analysts and other consumers. Works with key business stakeholders, IT experts, and subject-matter experts to plan, design, and deliver optimal analytics and data science solutions. Works on one or many product teams at a time. Though the role category is generally listed as Remote, this specific position is designated as Hybrid.
Key Responsibilities:
Business Alignment & Collaboration
Partner with the Product Owner to align data solutions with strategic goals and business requirements.Data Pipeline Development & Management
Design, develop, test, and deploy scalable data pipelines for efficient data transport into Cummins Digital Core (Azure DataLake, Snowflake) from various sources (ERP, CRM, relational, event-based, unstructured).Architecture & Standardization
Ensure compliance with AAI Digital Core and AAI Solutions Architecture standards for data pipeline design and implementation.Automation & Optimization
Design and automate distributed data ingestion and transformation systems, integrating ETL/ELT tools and scripting languages to ensure scalability, efficiency, and quality.Data Quality & Governance
Implement data governance processes, including metadata management, access control, and retention policies, while continuously monitoring and troubleshooting data integrity issues.Performance & Storage Optimization
Develop and implement physical data models, optimize database performance (indexing, table relationships), and operate large-scale distributed/cloud-based storage solutions (Data Lakes, Hadoop, HBase, Cassandra, MongoDB, Accumulo, DynamoDB).Innovation & Tool Evaluation
Conduct proof-of-concept (POC) initiatives, evaluate new data tools, and provide recommendations for improvements in data management and integration.Documentation & Best Practices
Maintain standard operating procedures (SOPs) and data engineering documentation to support consistency and efficiency.Agile Development & Automation
Use Agile methodologies (DevOps, Scrum, Kanban) to drive automation in data integration, preparation, and infrastructure management, reducing manual effort and errors.Coaching & Team Development
Provide guidance and mentorship to junior team members, fostering skill development and knowledge sharing.
External Qualifications and Competencies
Competencies:
System Requirements Engineering:
Translates stakeholder needs into verifiable requirements, tracks status, and assesses impact changes.Collaborates:
Builds partnerships and works collaboratively with others to meet shared objectives.Communicates Effectively:
Delivers multi-mode communications tailored to different audiences.Customer Focus:
Builds strong customer relationships and provides customer-centric solutions.Decision Quality:
Makes good and timely decisions that drive the organization forward.Data Extraction:
Performs ETL activities from various sources using appropriate tools and technologies.Programming:
Develops, tests, and maintains code using industry standards, version control, and automation tools.Quality Assurance Metrics:
Measures and assesses solution effectiveness using IT Operating Model (ITOM) standards.Solution Documentation:
Documents knowledge gained and communicates solutions for improved productivity.Solution Validation Testing:
Validates configurations and solutions to meet customer requirements using SDLC best practices.Data Quality:
Identifies, corrects, and manages data flaws to support effective governance and decision-making.Problem Solving:
Uses systematic analysis to determine root causes and implement robust solutions.Values Differences:
Recognizes and leverages the value of diverse perspectives and cultures.
Education, Licenses, Certifications:
- Bachelor's degree in a relevant technical discipline, or equivalent experience required.
- This position may require licensing for compliance with export controls or sanctions regulations.
Additional Responsibilities Unique to this Position
Preferred Experience:
Technical Expertise
Intermediate experience in data engineering with hands-on knowledge of SPARK, Scala/Java, MapReduce, Hive, HBase, Kafka, and SQL.Big Data & Cloud Solutions
Proven ability to design and develop Big Data platforms, manage large datasets, and implement clustered compute solutions in cloud environments.Data Processing & Movement
Experience developing applications requiring large-scale file movement and utilizing various data extraction tools in cloud-based environments.Business & Industry Knowledge
Familiarity with analyzing complex business systems, industry requirements, and data regulations to ensure compliance and efficiency.Analytical & IoT Solutions
Experience building analytical solutions with exposure to IoT technology and its integration into data engineering processes.Agile Development
Strong understanding of Agile methodologies, including Scrum and Kanban, for iterative development and deployment.Technology Trends
Awareness of emerging technologies and trends in data engineering, with a proactive approach to innovation and continuous learning.
Technical Skills:
Programming Languages:
Proficiency in Python, Java, and/or Scala.Database Management:
Expertise in SQL and NoSQL databases.Big Data Technologies:
Hands-on experience with Hadoop, Spark, Kafka, and similar frameworks.Cloud Services:
Experience with Azure, Databricks, and AWS platforms.ETL Processes:
Strong understanding of Extract, Transform, Load (ETL) processes.Data Replication:
Working knowledge of replication technologies like Qlik Replicate is a plus.API Integration:
Experience working with APIs to consume data from ERP and CRM systems.
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