We are looking for a talented Data Modeler/Data Architect to join our team
specializing in Systems/Information Technology for Cummins, Inc. as part of DBU
Data & Analytics, Remote.
In this role, you will make an impact in the following ways:
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, NoSQL databases).
Drive automation and modernization of data infrastructure and integration
processes to support agile analytics initiatives.
RESPONSIBILITIES
To be successful in this role you will need the following:
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.
QUALIFICATIONS
Education/Experience:
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.
Additional Responsibilities:
Preferred Job Specific Skills – Data Architect
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 (PageRank, community detection, pathfinding),
and integration of graph workloads with analytical and relational systems.
Microsoft Fabric Ecosystem — Practical experience with Fabric Lakehouse
architecture, Delta Lake optimization, Data Engineering pipelines, Data
Factory orchestration, KQL‑based Real‑Time Analytics, semantic model
creation, and integration with Power BI and OneLake governance.
SAP S/4HANA Data Structures —Familiarity of SAP S/4HANA data models (FI/CO,
MM, SD, PP), CDS views, OData services, SLT/SDI/ODP‑based extraction
patterns, and harmonization of SAP transactional data into cloud‑based
analytical platforms.
Cloud Data Architecture — Strong understanding of distributed data
processing, ELT/ETL orchestration, event‑driven ingestion (Kafka/Event Hub),
metadata‑driven frameworks, schema evolution, and data lifecycle management
across cloud environments (Azure preferred).
Data Governance & Metadata Management — Experience implementing enterprise
data catalogs, lineage tracking, data quality rules, master data integration,
and security models (RBAC/ABAC, row‑level and column‑level security).
Performance Engineering & Optimization — Ability to diagnose bottlenecks
across compute, storage, and network layers; optimize workloads for cost and
performance; and design scalable, fault‑tolerant data architectures.
Cross‑Platform Integration — Experience integrating heterogeneous systems
(SAP, Snowflake, Fabric, graph DBs, APIs, streaming platforms) into unified
analytical ecosystems with strong focus on interoperability and data
consistency.
Compensation:
Please note that the salary range provided is a good faith estimate on the
applicable range. The final salary offer will be determined after considering
relevant factors, including a candidate’s qualifications and experience, where
appropriate.
Premium Range:
Minimum: $123,030
Maximum: $150,370
Cummins is an equal opportunity employer. Our policy is to provide equal
employment opportunities to all qualified persons without regard to race, sex,
color, disability, national origin, age, religion, union affiliation, sexual
orientation, veteran status, citizenship, gender identity, or other status
protected by law.