Sr. Data Engineer

Senior Data EngineerA well-established organization in the energy and utilities industry is seeking a Senior Data Engineer to join its analytics team. This is an opportunity to work on meaningful, high-impact data initiatives that influence operational performance, reliability, risk management, and business decision-making.The Senior Data Engineer will design, develop, and support data solutions that transform complex operational information into reliable, actionable insights. This individual will work across data engineering, business intelligence, statistical analysis, and emerging AI technologies.A key focus of the role will be analyzing data related to reliability and vegetation management programs, evaluating the impact of operational changes, and developing analytics that help stakeholders understand performance, risk, customer impact, and opportunities for improvement.The ideal candidate is an experienced data professional who can work independently, solve complex problems, and translate ambiguous business questions into practical technical solutions.Key responsibilities include:Build and maintain scalable data pipelines, analytical datasets, and reporting solutions.Write and optimize SQL queries while investigating data quality and transformation issues.Develop Power BI dashboards, reports, semantic models, and other business intelligence solutions.Work with data from multiple enterprise systems and sources to create comprehensive analytical views.Perform statistical analysis to measure operational performance and determine the effectiveness of business initiatives.Analyze reliability, outage, asset, vegetation, customer, and operational data to identify trends and potential risks.Develop meaningful performance indicators and analytical models that supplement traditional reliability measurements.Create dashboards, scorecards, rankings, and visualizations that help business leaders prioritize actions.Validate data, reconcile discrepancies between systems, and document assumptions and business logic.Translate business needs into repeatable data models, analytical processes, and user-friendly solutions.Support production data environments through troubleshooting, quality checks, version control, and ongoing improvements.Collaborate with technical teams and business stakeholders to gather requirements and deliver effective solutions.Leverage AI-assisted development and emerging technologies to improve data engineering and analytical capabilities.Qualifications include:Senior-level experience in data engineering, data analytics, business intelligence, or a related field.Strong SQL development and data troubleshooting experience.Experience with ETL/ELT processes and data pipeline development.Experience with Power BI and/or Microsoft Fabric.Knowledge of data modeling and modern enterprise data environments.Ability to use AI tools or prompting techniques to assist with programming and data-related tasks.Strong analytical, problem-solving, and critical-thinking skills.Ability to independently research, investigate, and resolve complex data challenges.Excellent communication skills with both technical and non-technical audiences.Strong attention to detail and commitment to data accuracy.Self-motivated with the ability to work effectively with limited supervision.Preferred qualifications include:Experience with Minitab Statistical Software or a similar statistical analysis platform.Experience with Snowflake and enterprise data warehousing.Experience with Microsoft Fabric, Lakehouse environments, or cloud-based data solutions.Experience working with SAP or other large enterprise systems.Experience with GIS or geospatial data.Utility, energy, infrastructure, engineering, or other asset-intensive industry experience.Knowledge of electric reliability concepts and operational performance metrics.Experience developing predictive, leading, or customer-focused reliability indicators.Familiarity with AI platforms, machine learning, predictive analytics, or intelligent automation.Additional details include:This position is structured as contract-to-hire, with the potential for permanent employment based on business needs and performance.The initial schedule is expected to be 4 days onsite and 1 day remote. Additional remote flexibility may become available after approximately six months but is not guaranteed.The anticipated start date is October 2026, with potential flexibility for an earlier start.The interview process includes two interviews and a practical data exercise.Candidates should be prepared to demonstrate their technical, analytical, and problem-solving abilities.This is a senior-level position, and the selected candidate is expected to be productive with minimal training.Perks include:Work on high-impact data initiatives with measurable business and operational outcomes.Opportunity to work across data engineering, analytics, statistics, and emerging AI technologies.Exposure to modern data platforms and enterprise analytics environments.Potential pathway from contract to permanent employment.Hybrid work flexibility.Opportunity to directly influence reliability, operational performance, and strategic decision-making.