> Markdown version of [/jobs/ext/178075-principal-data-architect-battery-storage](https://www.wearedevelopers.com/jobs/ext/178075-principal-data-architect-battery-storage). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal Data Architect - Battery Storage

- **Company:** Plus
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $170,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Data Analysis, CAN Bus, Cloud Database, Databases, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Integration, Dimensional Modeling, Python (Programming Language), PostgreSQL, Metadata, Modbus, Rapid Application Development, Reference Data, Cloud Services, Standard Sql, SQL Databases, Data Storage Technologies, Snowflake, Data Strategy, Data Layers, AWS Aurora, Influxdb, Data Management
- **Published:** May 31, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b40b740bf79632ff

## About the Role

Do you have experience in Working in the energy & utilities sector?, * 8+ years of experience in data engineering, data architecture, or analytics platform development, with demonstrated ownership of cross-team data standards and models

 * Strong expertise in analytical data modeling, including dimensional modeling, semantic layers, and schema design for multi-consumer analytics use cases
 * Deep working knowledge of SQL and experience collaborating on or authoring complex analytical queries and models
 * Proven experience designing or contributing to analytics platforms built on Snowflake or similar cloud data warehouses using ELT-based architectures
 * Experience defining and operationalizing data catalogs, metadata, and shared definitions, including naming conventions, ownership models, and documentation practices
 * Experience designing or supporting data governance frameworks, including data quality, ownership, lifecycle management, and schema change management
 * Experience supporting application teams on schema design to enable rapid application development and reliable data integration
 * Familiarity with analytics engineering practices and tools (e.g., dbt or similar modeling frameworks)
 * Proficiency with Python for data analysis, modeling, validation, or prototyping (not limited to production pipeline code)
 * Experience partnering closely with data engineers on ELT patterns, schema evolution, and data quality practices
 * Experience working with PostgreSQL or compatible systems (including managed services such as AWS Aurora) and understanding how operational schemas interact with analytical models
 * Knowledge of AWS data services and cloud-native data patterns strongly preferred
 * Demonstrated ability to work effectively with data analysts across a wide range of technical skill levels, including analysts with limited engineering backgrounds
 * Strong communication skills and a track record of cross-functional collaboration with engineering, analytics, and business stakeholders
 * Experience working in environments with large, diverse analyst populations and high data consumption across teams preferred
 * Proven ability to deliver incremental architectural improvements while maintaining a clear long-term vision for data consistency and scalability
 * Background in energy, finance, trading, or other data-intensive, operationally complex domains preferred

## Description

* Define and evolve data architecture standards for analytics and reporting, including data modeling, naming conventions, schema design, and documentation practices across the organization
 * Own the data catalog and metadata strategy, partnering with stakeholders to define, name, and organize data assets across multiple domains and source systems
 * Collaborate closely with Principal Data Engineering leadership and application engineering teams to align on ELT patterns, Snowflake usage, schema evolution, and analytical data modeling practices
 * Contribute hands-on through SQL and Python, developing reference data models, prototypes, templates, and example implementations that demonstrate architectural intent
 * Support and enable data analysts by establishing consistent data usage, modeling standards, and shared definitions across a wide range of technical skill levels
 * Partner with application engineers on schema design to support rapid application development and reliable integration between operational and analytical data systems
 * Support PostgreSQL (including AWS Aurora) and Snowflake data modeling and analytical access patterns in collaboration with platform and database stakeholders
 * Establish and promote data governance practices covering data quality, ownership, lifecycle management, and schema change management
 * Drive incremental delivery of data architecture improvements, aligning short-term progress with a clear long-term architectural vision
 * Design high-ingestion pipelines (using tools like InfluxDB, Timescale, or Snowflake) capable of handling millions of data points per second from globally distributed battery sites
 * Ensure data can be seamlessly ingested from various industrial protocols such as Modbus, CAN bus, or DNP3, and translated into standardized cloud formats
 * Ensure data architectures comply with grid-specific regulations (like NERC CIP) and mandate on-site data storage for grid resilience
 * Help set the vision, roadmap and communicate the enterprise data strategy for the company


## Related Videos

- [Optimizing Land-Based Fish Feeding with Node-RED](https://www.wearedevelopers.com/videos/2032-optimizing-land-based-fish-feeding-with-node-red)
- [A Hitchhikers Guide to Container Security - Automotive Edition 2024](https://www.wearedevelopers.com/videos/1119-a-hitchhikers-guide-to-container-security-automotive-edition-2024)
- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)
- [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post)
- [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering)
- [Developer Tools for Microsoft Azure](https://www.wearedevelopers.com/videos/450-developer-tools-for-microsoft-azure)

## Related Articles

- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)
- [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)
- [A Guide to Green Tech and Green IT Careers](https://www.wearedevelopers.com/magazine/374-a-guide-to-green-tech-and-green-it-careers)