AES Clean Energy (CE) is seeking a Senior Analytics Engineer to support the Operations and Maintenance (O&M) Engineering team in building the data analytics architecture to support the future growth of the CE portfolio and its growing data-related needs. This individual will play a pivotal role in ensuring AES CE's operational excellence by expanding the availability of data and analytics to various stakeholders in the O&M team. The ideal candidate will be a self-starter with an ability to deliver creative, efficient solutions to challenging problems surrounding the growing operational dataset. A day in the life of an AES CE Sr. Analytics Engineer will include, but is not limited to: Designing, building and maintaining data warehouses, data cleansing processes, analytics dashboards, pipelines, and automated reporting solutions Support high data quality, reliability, and availability across CEDAR and related automated workflows Owning and administrating core data engineering and analytics platforms used by the Data Analytics team Collaborating with Analytics Engineering, O&M Engineering, and Digital teams to deliver scalable data solutions Working on AI/Machine Learning projects to improve the performance of the AES Clean Energy fleet of solar, wind, and energy storage assets The Sr. Analytics Engineer supports a larger O&M team and serves as the subject matter expert for data-related aspects of operating and monitoring clean energy plants. This requires knowledge and experience working with SCADA/DAS systems, data warehouses, reporting tools, and other advanced analytics and data infrastructure tools (i.e. Power BI, SQL, R and Python). Excellent communication, task management and planning skills needed, in addition to technical breadth. The position may include up to 5-10% travel to partner offices and project locations. Key Responsibilities Operations • Work with AES Data Engineers to establish and maintain data warehouses to support the O&M team's advanced analytics and reporting needs • Build scalable, automated reporting solutions to meet the growing compliance demands of the CE Asset Management group • Establish and monitor data quality frameworks, data governance, validation processes, and system performance metrics • Ensure scalable, reliable ingestion and processing of operational data from SCADA, DAS, and other external data sources to the GCP data lake • Participate in and lead AI/Machine Learning initiatives in collaboration with the AES Digital Team and O&M team stakeholders • Become an expert in AES Clean Energy's DAS tools and propose ways to improve their data quality, overall function and utilization Collaboration • Collaborate with the Analytics Engineering team to ensure data products are built on scalable, reliable infrastructure • Together with the CE Operations Technology and Data Engineering teams, work to deliver successful data pipelines from SCADA/DAS providers to data warehouses • Work cross functionally to create scalable data infrastructure and workflows • Provide technical support and maintenance of automated reporting systems utilized by the CE Asset Management group • As a subject matter expert, advise other team members across the organization on best practices for data-related projects Growth and Leadership • Participate in AES CE's growth planning process by contributing to process improvement task forces and other strategic planning activities • Improve and develop processes for utilizing data to ensure the operation of safe, quality and high-performance projects • Willingness to continue to learn and grow your skills, constantly evaluating how AES CE operations can be improved Skills and Qualifications Primary Qualifications • Undergraduate degree in Engineering, Computer Science, or equivalent technical field and 5+ years of experience in an analytics-focused and/or engineering role • Advanced proficiency with R, Python, or SAS, as well as SQL • Advanced proficiency developing reports and dashboards in Power BI, Tableau, Qlik Sense or another BI software • Strong familiarity with DAS and SCADA systems and their data architectures • Experience with Google Cloud Platform, Big Query, or other cloud computing platforms • Experience designing and maintaining scalable data pipelines (ETL/ELT) and utilizing related tools (e.g., DBT, Prefect, Airflow) • Strong analytical thinking and problem-solving skills • Experience designing data models, analytics datasets, data products, or application layers • Experience building or owning production data pipelines, data platforms, or analytics systems • Ability to work effectively with Microsoft software programs, including-but-not-limited-to Excel, Outlook, Word, and PowerPoint • Excellent written and verbal communication skills • High degree of commitment to a quality safety culture and an incident-free work environment • Personal values consistent with those of the AES Corporation "Plus" Qualifications • Advanced degree in Engineering, Computer Science, Data Science, or equivalent • Experience with the technical aspects of Solar PV, Wind, and Energy Storage Systems • Experience with AI/ML-enabled analytics, including LLMs, RAG, and anomaly detection • Spanish language skills The expected salary for this position, at commencement of employment, is between $113,000 and $141,525/year; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position also includes annual bonus. The benefits offered for this position are: medical, dental, and vision coverage, life insurance, 401(k) eligibility, and paid time off (including vacation, sick leave time, and parental leave). Details of participation in these benefit plans will be provided if a candidate receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Apply by clicking the application link below and submitting your information. The deadline to apply for this role is 09/23/2026