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.
