Data Architect

🕒 3 days ago

🏈 Alabama, Alaska, +44 more states – Remote

🏈 Alabama – Remote 🐻 Alaska – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌺 Hawaii – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🌾 Iowa – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote ⚜️ Louisiana – Remote 🦞 Maine – Remote 🦬 Montana – Remote 🌾 Nebraska – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🌶️ New Mexico – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🌾 North Dakota – Remote 🏈 Ohio – Remote 🌪️ Oklahoma – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🌴 South Carolina – Remote 🗿 South Dakota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

💵 $123k - $150.4k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Cummins Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1919

🏗️ Construction

💼 Consulting

🏥 Healthcare

💰 $75M Grant on 2024-07

Construction • Consulting • Healthcare

Cummins Inc. is a global power technology leader that designs, manufactures, and distributes a variety of engines and power systems solutions. They offer products that range from diesel and natural gas engines to hybrid and electric power systems, as well as components like turbochargers, fuel systems, and emissions solutions. With a strong emphasis on innovation, Cummins aims to reduce emissions and improve fuel efficiency. The company is dedicated to helping industries navigate the transition to cleaner energy through integrated power solutions suitable for diverse applications such as on-highway, marine, mining, and construction. Additionally, Cummins provides services including remote monitoring, diagnostics, and aftermarket support, reinforcing its commitment to sustainability and customer service excellence.

📋 Description

• 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 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 for stability and performance • Develop and manage large-scale data storage solutions using distributed and cloud platforms, including data lakes, Hadoop, and NoSQL databases • Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives • Build scalable, automated ETL pipelines delivering accurate, timely data • Write clean, well-documented, and testable code using best practices, version control, and automation • Follow SDLC standards to test and validate solutions against business requirements and production performance • Monitor and resolve data issues and establish governance practices to maintain data accuracy and trust

🎯 Requirements

• College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent experience required • Intermediate experience in a relevant discipline area required • 6–8 years of experience required • Familiarity analyzing complex business systems, industry requirements, and/or data regulations • Background processing and managing large data sets • Experience designing and developing Big Data platforms using open-source and third-party tools • Experience with Spark, Scala/Java, MapReduce, Hive, HBase, and Kafka, or equivalent college coursework • SQL query language proficiency • Clustered compute cloud-based implementation experience • Experience developing applications requiring large file movement in cloud-based environments • Experience with data extraction tools and methods from varied sources • Experience building analytical solutions • Preferred experience with IoT technology and Agile software development • Deep expertise in enterprise-scale dimensional modeling • Advanced SQL engineering, including window functions, CTEs, query plan analysis, optimization, partitioning, and performance tuning • Hands-on Snowflake architecture and engineering experience • Strong experience with Neo4j or equivalent graph platforms and Cypher • Practical Microsoft Fabric experience, including Lakehouse, Delta Lake, Data Factory, KQL, Power BI, and OneLake • Familiarity with SAP S/4HANA data models, CDS views, OData, and extraction patterns • Strong understanding of cloud data architecture, distributed processing, ETL/ELT orchestration, event-driven ingestion, schema evolution, and data lifecycle management • Experience implementing data catalogs, lineage tracking, data quality rules, master data integration, and RBAC/ABAC security models • Ability to diagnose and optimize compute, storage, and network bottlenecks • Experience integrating SAP, Snowflake, Fabric, graph databases, APIs, and streaming platforms • May require licensing for export-control or sanctions compliance

🏖️ Benefits

• Equal employment opportunity employer • Remote/off-site work arrangement • No relocation required ("Relocation Eligible?" — No)