Data Architect

We are looking for a talented Data Architect to join our team specializing in Systems/Information Technology for Cummins, Inc. as part of DBU Data & Analytics, Remote.

• Design and automate scalable data ingestion and transformation pipelines across relational, event-based, and unstructured sources.
• Build and maintain frameworks to monitor, detect, and resolve data quality and integrity issues. Implement data governance practices, including metadata management, data access, and retention policies.
• Architect and guide development of reliable, efficient, and scalable ETL/ELT data pipelines with monitoring and alerting.
• Design physical data models and optimize database structures, indexing, and relationships for performance.
• Test, optimize, and troubleshoot data pipelines to ensure stability and performance.
• Develop and manage large-scale data storage solutions using distributed and cloud platforms (e.g., data lakes, Hadoop, No
  
  SQL databases).
• Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives.

• Data Extraction
  - Build scalable, automated ETL pipelines that deliver accurate, timely data. Choose the right tools and optimize transformations for performance and usability.
• Programming
  - Write clean, well‑documented, and testable code using best practices. Leverage version control and automation to ensure reliability and efficiency
• Solution Validation Testing
  - Follow SDLC standards to thoroughly test and validate all solutions. Ensure outputs meet business requirements and perform correctly in production.
• Data Quality
  - Proactively monitor and resolve data issues. Establish strong governance practices to maintain data accuracy and trust across the organization.

• College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required.
• This position may require licensing for compliance with export controls or sanctions regulations.
• Intermediate experience in a relevant discipline area is required. Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:
  Familiarity analyzing complex business systems, industry requirements, and/or data regulations
  Background in processing and managing large data sets
  Design and development for a Big Data platform using open source and third‑party tools
  SPARK, Scala/Java, Map‑Reduce, Hive, Hbase, and Kafka or equivalent college coursework
  SQL query language
  Clustered compute cloud‑based implementation experience
  Experience developing applications requiring large file movement for a Cloud‑based environment and other data extraction tools and methods from a variety of sources
  Experience in building analytical solutions
  Intermediate experiences in the following are preferred:
  
  Experience with IoT technology
  Experience in Agile software development
• 6-8 years of experience required.

• Dimensional Modeling Mastery — Deep expertise in designing enterprise‑scale dimensional models (star, snowflake, constellation) with strong command of fact table grain definition, surrogate key strategies, slowly changing dimensions (Types 1–6), bridge tables, and late‑arriving data handling.
• Advanced SQL Engineering — Highly proficient in writing complex, high‑performance SQL, including window functions, CTE‑driven transformations, query plan analysis, cost‑based optimization, partitioning strategies, and performance tuning across large, distributed datasets.
• Snowflake Architecture & Engineering — Hands‑on experience with Snowflake internals including micro‑partitioning, clustering keys, result‑set caching layers, warehouse sizing/auto‑suspend tuning, Snowpipe/Streams/Tasks orchestration, Time Travel, Zero‑Copy Cloning, and secure data sharing patterns.
• Graph Database & Cypher Proficiency — Strong experience with Neo4j or equivalent graph platforms, including graph schema design, Cypher query optimization, graph algorithms (Page Rank, community detection,…