Data Analyst
Omni Inclusive, Minneapolis, MN, United States
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. re there any specific companies you like to see on a candidate's resume?
None
5. re there any certifications that the candidate must possess?
None
6. re 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
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. re there any specific companies you like to see on a candidate's resume?
None
5. re there any certifications that the candidate must possess?
None
6. re 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