Senior Analyst, Analytics Engineering

Clearway Energy•Scottsdale, AZ

1d•Hybrid

About The Position

Clearway Energy Group is seeking a Senior Analyst, Analytics Engineering to translate business questions into trusted data models, reporting, dashboards, and lightweight predictive analyses. The role partners primarily with asset managers and also with Commercial Analytics (CA), Market Optimization and Trading (MOT), commercial, finance, accounting, procurement, and operations stakeholders. The initial workload is expected to be divided approximately equally among revenue analytics and stakeholder reporting; modeling SAP data across accounting, procurement, and operations and maintenance (O&M); and monthly curtailment reporting. Priorities may change with business needs. This is a hands-on hybrid position based in the Scottsdale, Arizona office, with three days per week in the office. It combines data analysis, visualization, and requirements gathering with analytics engineering using SQL, dbt, version control, and documentation. The modern data stack includes Snowflake, dbt, Hex, Streamlit, and GitLab. The role is intended for an analyst who has independently delivered reliable reporting and analytical solutions and wants to expand ownership of data modeling and analytics engineering while working closely with business stakeholders. The position includes developing and maintaining dbt models and Snowflake datasets, building revenue and commercial performance analyses and dashboards, producing monthly fleet curtailment reports, and using Python for automation and lightweight analytical prototypes. It also involves documenting data assets, following data classification and access-control standards, and working with data engineering and source-system owners to address data quality issues. The role is eligible for an annual cash bonus subject to personal and company performance goals. No visa sponsorship or other employment authorization sponsorship is available now or in the future.

Requirements

Bachelor’s degree in Engineering, Computer Science, Data Science, Finance, Accounting, Economics, Business, or a related quantitative field.
At least 3 years of relevant experience in data analysis, business intelligence, or analytics engineering, including a track record of independently delivering reliable analytical work.
Strong SQL skills, including joins, window functions, common table expressions, and query optimization; experience with a cloud data warehouse, preferably Snowflake.
Hands-on experience building and maintaining dbt models, including dbt data tests and documentation.
Working knowledge of dimensional modeling and analytics-ready data structures.
Proficiency in Python for data analysis and scripting, such as with pandas, NumPy, Matplotlib, or Plotly.
Hands-on Git experience, including branching, pull or merge requests, and code review.
Ability to responsibly use approved AI coding tools, review and test code, validate results, and protect sensitive data.
Strong Excel skills for building, reviewing, and quality-checking report workbooks.
Experience building dashboards and reports using a modern BI or visualization tool, such as Hex, Power BI, Tableau, Spotfire, or Streamlit.
Demonstrated ability to work with business stakeholders to clarify ambiguous requests and deliver suitable outcomes.
Commitment to clear documentation of data models, metrics, and analyses.
Ability to explain technical concepts to non-technical audiences.
Self-directed and detail-oriented, comfortable managing multiple priorities, and able to work in the Scottsdale office three days per week.

Nice To Haves

Experience modeling data from SAP or a comparable ERP, such as Oracle, NetSuite, or Workday, for accounting, procurement, or maintenance reporting.
Experience with high-frequency time-series data, such as one- to five-minute data, or renewable operational data such as SCADA or historian data, power curves, or availability calculations.
Familiarity with curtailment, PPA terms, ISO/RTO markets such as CAISO or ERCOT, or LMP data.
Experience in energy, utilities, or financial services, including energy markets, trading, asset performance, or O&M data.
Experience with revenue, financial, or commercial analytics.
dbt Analytics Engineering Certification.
Exposure to workflow orchestration tools such as Dagster or Airflow.
Experience with forecasting or predictive modeling, such as scikit-learn or statsmodels.
Experience building data applications with Streamlit.

Responsibilities

Partner with asset managers and business stakeholders across Commercial Analytics, Market Optimization and Trading, commercial, finance, accounting, procurement, and operations to clarify questions and define requirements, metrics, and deliverables.
Manage a backlog of reporting and analysis requests, prioritize work with the manager, communicate scope and timelines, and explain tradeoffs.
Present findings and recommendations clearly to technical and non-technical audiences.
Develop analyses and reporting on revenue and commercial and trading performance metrics, including variance and trend analysis.
Build and maintain dashboards and self-service data applications, such as Hex and Streamlit, and apply sound data visualization practices.
Support recurring and ad hoc reporting requests, including those from senior management.
Develop and maintain dbt models that transform raw data into documented, business-ready staging, intermediate, and mart datasets.
Model SAP data in Snowflake for accounting, procurement, and O&M reporting; translate SAP structures into intuitive analytical models.
Work with finance, accounting, procurement, and O&M subject-matter experts to define data mappings and reconciliation rules.
Write performant SQL for Snowflake in accordance with team conventions and Snowflake best practices.
Implement dbt data tests and source freshness checks, including reconciliation of analytical models to SAP source totals.
Use Git and GitLab for version control and analytics-code review.
Apply established site-specific curtailment methodologies to produce monthly reports for the wind, solar, and solar-plus-storage fleet, including reruns and backfills, for review and release by the Commercial Analytics manager.
Validate curtailment inputs and results, including prediction error, missing or stuck values, timestamp coverage, and dispatch data.
Troubleshoot failed reporting runs and improve the reliability, automation, and documentation of reporting scripts.
Use Python to automate data preparation, build analysis scripts, and prototype lightweight forecasting and statistical models.
Use approved AI coding tools responsibly and review, test, and validate generated code and outputs before production use or delivery to stakeholders.
Partner with senior team members to move validated prototypes into maintained, documented workflows.
Maintain model documentation, metric definitions, data dictionaries, and onboarding materials.
Follow data classification and access-control standards when handling sensitive commercial and financial data.
Flag data quality issues early and work with data engineering and source-system owners to resolve root causes.

Benefits

Generous paid time off.
Medical, dental, and vision care.
Health savings accounts with company contributions.
Health and dependent daycare flexible spending accounts.
Commuter benefits.
Relocation assistance.
401(k) plan with employer match.
Life and accident insurance.
Fertility programs.
Adoption assistance.
Parental leave.
Tuition reimbursement.
Benefits for employees in same-sex marriages, civil unions, and domestic partnerships.
Company-provided meals and events for office-based employees.
Annual cash bonus eligibility, subject to personal and company performance goals.