Summit Utilities Inc is seeking a Senior Data Engineer to lead the design, implementation, and ongoing modernization of enterprise data pipelines and platform standards across cloud and on-prem environments. This hybrid role is based in Arkansas, with options in Little Rock, Fort Smith, or Fayetteville, and focuses on empowering operations, analytics, and regulatory reporting while mentoring engineers and coordinating with cross-functional teams.
Responsibilities
- Lead end-to-end pipeline architecture for enterprise-scale workloads across cloud and on-prem environments, defining storage models, partitioning strategies, and orchestration patterns.
- Define data engineering strategy and technical direction for functional areas, leading platform modernization initiatives and approving pipeline deployments to production.
- Drive Python and SQL development standards across the team, including advanced transformation logic, custom frameworks, and reusable libraries for ingestion and integration.
- Architect cloud-based data services (Azure, AWS, Microsoft Fabric) with infrastructure-as-code, monitoring, alerting, and governance frameworks.
- Define platform-level pipeline standards for error handling, logging, alerting, data validation, and data lifecycle management across all enterprise data flows.
- Lead cross-system integration efforts with SAP, GIS, SCADA, AMI, and external vendor systems via APIs, secure file exchanges, and cloud-native connectors.
- Serve as a formal mentor for Data Engineers I–III through code reviews, design sessions, and technical career coaching; may direct the work of 1–2 contractors or junior staff.
- Partner with Data Architects, Analytics Engineers, and IT leadership on platform standards, tooling decisions, and the long-term data engineering roadmap.
- Evaluate and select technologies for ingestion, orchestration, observability, and CI/CD; drive adoption and rollout across the data engineering team.
- Support regulatory filings (PHMSA, FERC, state PUC) and pipeline integrity data management with reliable, auditable, and well-documented data infrastructure.
- Investigate complex, system-wide performance and reliability issues; lead troubleshooting efforts and recommend long-term architectural solutions.
Requirements
- Bachelor’s degree in computer science, Information Systems, Engineering, or a related field preferred; equivalent combination of education and relevant experience will be considered.
- 8–12 years of experience in data engineering, software development, or enterprise data integration roles.
- Extensive hands-on experience designing, building, and operating cloud data pipelines at enterprise scale.
- Proven track record architecting scalable enterprise data solutions across Azure and/or AWS environments.
- Strong experience integrating data from relational systems, cloud-native services, SAP, GIS, SCADA, and AMI.
- Demonstrated leadership delivering cross-functional data engineering programs and establishing development standards.
- Hands-on experience with infrastructure-as-code, CI/CD, source control, and automated deployment workflows.
- Master’s degree in a quantitative or technical field is preferred.
- Advanced Python and SQL mastery, including complex transformation logic, performance tuning, and reusable framework development.
- Expert cloud architecture skills across Azure and/or AWS, including data services, networking, security, and cost optimization.
- Deep expertise in designing end-to-end pipeline architecture for enterprise scale, including storage model design, partitioning strategies, and orchestration patterns.
- Proven leadership in cross-system integration spanning SAP, GIS, SCADA, AMI, and customer data systems.
- Hands-on experience with infrastructure-as-code (Terraform, Bicep, or similar) and platform monitoring & governance frameworks.
- Strong understanding of CI/CD, source control, and automated testing for data pipelines and platform components.
- Demonstrated ability to architect resilient, scalable, and cost-efficient data solutions, including CU tuning in Microsoft Fabric and other cloud platforms.
- Skilled at translating regulatory and business requirements into durable, well-governed data infrastructure; experience supporting PHMSA, FERC, and state PUC filings is preferred.
- Proven mentor and peer leader with experience guiding Data Engineers I–III through code reviews, design sessions, and career development.
- Strong written and verbal communication skills with a demonstrated ability to influence technical and business stakeholders, including VP/Director-level partners.
- Deep working knowledge of natural gas distribution and utility data systems (billing, AMI, SCADA, SAP, GIS) and pipeline integrity data management.
- Strong problem-solving and root cause analysis skills for complex, distributed enterprise systems.
- Friendly, solution-oriented team player aligned with Summit’s PEAKS values.
Technologies
- Python
- SQL
- Azure
- AWS
- Microsoft Fabric
- Terraform
- Bicep
- CI/CD
- SAP
- GIS
- SCADA
- AMI
- APIs
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Competitive pay
Position Summary
Summit Utilities seeks a Senior Data Engineer to own the design, implementation, and ongoing modernization of enterprise data pipelines and platform standards supporting operational, analytical, and regulatory workloads. The role oversees end-to-end pipeline architecture across cloud and on-prem environments, sets technical direction for storage models, partitioning, orchestration, and cross-system integration, and approves pipeline deployments to production. As a formal mentor for Data Engineers I–III, the position collaborates with Data Architects, Analytics Engineers, and IT leadership on platform standards, evaluates technologies, and supports regulatory filings (PHMSA, FERC, state PUC) with reliable, well-governed data infrastructure. Ideal candidates bring 8–12 years of experience with advanced Python and SQL mastery, deep Azure/AWS cloud architecture expertise, infrastructure-as-code, CI/CD, and a proven track record of delivering scalable enterprise data solutions in a regulated environment.
