About the Role
The Opportunity
Would you like a side hustle working with a new consulting startup that is building something different? If you are the person people call when the data is messy, the process is broken, and no one knows where to start, we would love to talk. If you have spent 10 or more years building a reputation for solving difficult problems, creating leverage through automation, and delivering results that make stakeholders say “wow,” this may be the opportunity you are looking for.
We offer the opportunity to work 15–20 hours per week, fully remote, while maintaining your current day job if you choose. We are creating a new type of part-time opportunity for deeply experienced data professionals who enjoy solving hard problems, moving quickly, and producing results that matter.
This is not an environment where success is measured by meetings attended, years of tenure, or navigating organizational politics. We care about outcomes. We hire people who consistently deliver high-quality work, take ownership, and can accomplish in a few hours what often takes others days. If you are the person your team trusts to untangle complexity, automate the tedious, and figure things out when there is no playbook, you will fit right in.
You will work alongside talented, experienced colleagues across analytics, engineering, GIS, automation, AI, product development, and business transformation. Most of our team brings 10 to 30 years of hands-on experience. We intentionally keep our teams small, our standards high, and our focus on delivering measurable value for clients.
What You Will Do
Design and implement automation that reduces GIS editing effort and backlog.
Build Python-based validation, reconciliation, and quality-monitoring pipelines.
Create automated comparisons between engineering documents, job prints, and GIS records.
Identify systemic data-quality issues, determine root causes, and implement durable solutions.
Apply AI and automation techniques to accelerate document review, anomaly detection, and workflow execution.
Partner directly with utility stakeholders, GIS leaders, and engineering teams to solve complex business problems.
Establish scalable QA/QC frameworks, performance metrics, and reporting that improve accuracy and throughput.
What Success Looks Like
Data quality issues are identified before reaching downstream users.
Editors spend less time on manual review and more time solving meaningful problems.
Automation handles repetitive tasks that previously required significant manual effort.
Stakeholders trust the quality, repeatability, and transparency of the solutions delivered.
Required Qualifications
10+ years of post-education professional experience, with a decade or more focused on GIS, geospatial data, utility data, or closely related work.
7+ years of hands-on Python development, including production-grade automation and validation solutions.
5+ years leading complex data quality, automation, or process improvement initiatives.
Strong data management skills, including data modeling, data quality control, and handling large, complex datasets.
Proficiency in enterprise Geographic Information Systems (GIS) and geospatial data concepts and geodata management practices, with hands-on experience building spatial databases and geospatial data pipelines.
Advanced analytical skills for diagnosing data issues, evaluating data integrity, and supporting data-driven decision-making.
Highly self-directed. Able to navigate ambiguity and deliver with limited direction, while still collaborating openly as part of a small team.
Strong consulting, stakeholder management, and problem-solving capabilities.
Track record of delivering significant business impact and consistently performing at a high level.
Preferred Qualifications
Bachelor's or advanced degree in GIS, Geography, Geomatics, Computer Science, Data Analytics, Engineering, or a related field.
Utility industry experience supporting electric, gas, water, or telecommunications organizations.
Experience with ArcGIS Enterprise, ArcGIS Pro, Utility Network, and Data Reviewer.
Experience with Databricks, cloud data platforms, APIs, and modern analytical ecosystems.
Previous consulting, startup, or entrepreneurial experience.
Experience mentoring technical teams or leading specialized workstreams.
GISP certification or equivalent advanced credentials.
What This Role Is Not
Not a field collection or survey position.
Not a GIS technician or production editing role.
Not a full-stack application development position.
Not an early-career or junior opportunity. This role assumes a decade or more of practical GIS experience.