Data Analyst

Performs data collection, analysis, validation, cleansing, and reporting. Designs, codes, tests, debugs, and documents ETL processes, SQL queries, and stored procedures. Extracts and analyzes data from various sources, including databases, manual files, and external websites. Responds to data inquiries from various groups within an organization. Creates and publishes regularly scheduled and ad hoc reports. Documents reporting requirements and processes and validates data components as required. Requires experience with relational databases and knowledge of query tools and/or statistical software. Strong analytical and organizational skills also essential. Must possess expert level knowledge of MS Excel.

1. Explain what the scope of the work/project is? Project Overview, deliverables (what is this person responsible for).

This is a contract Data Analyst role supporting the Energy Efficiency side of the utility business, specifically residential solar and energy efficiency programs (rebates, incentives, high‐efficiency equipment).

The analyst will focus on:

Data quality and data governance

Contextualizing data so it is meaningful for business users

Documenting data dictionaries and validation rules

Identifying gaps in data pipelines and working with IT to resolve them

Building and maintaining data pipelines

Developing dashboards (Power BI)

Supporting self‐service analytics and training business users over time

This team acts as data stewards and subject matter experts, ensuring data is accurate, trusted, and valuable.

1. What are the top 3-5 skills and qualifications (technology/application/software, etc.) required?

SQL

Understanding of data governance and data quality

Python

Power BI

Databricks (nice to have; trainable)

2. What non-technical skills are necessary (i.e., such as communication, problem solving, team player)?

Strong communication skills

Ability to explain data in non‐technical language

Relationship‐building

Problem‐solving in ambiguous environments

Ability to professionally say "no” and scope work appropriately

Storytelling with data

3. Ideal candidate background and how many years required?

More junior‐level role

Around up to 3 years of experience, though flexible for strong candidates

Interest in data analytics or data science

Comfortable working with undocumented or messy data

4. Are there any specific companies you like to see on a candidate's resume?

None

5. Are there any certifications that the candidate must possess?

None

6. Are there any preferred or "nice to have" skills?

Databricks experience

Jira familiarity

Experience with data pipeline development

Exposure to analytics in regulated industries

Training or enablement experience