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17 hours ago
We are seeking a skilled Technical Project Manager to lead our geospatial data collection processes. The ideal candidate will have experience in designing and implementing efficient workflows, collaborating with cross-functional teams, and driving process automation.
Key Responsibilities:- Workflow Design and Implementation: Develop and implement efficient workflows for large-scale geospatial data collection processes, including geocoding, transit data management, and Points of Interest (POI) collection.
- Cross-Functional Collaboration: Collaborate with GIS engineers, data analysts, and product managers to define and enforce best practices in data collection and quality assurance.
- Process Automation: Drive the automation of manual workflows, ensuring consistency and accuracy in data processing pipelines.
- Integration and Evaluation: Evaluate and integrate third-party tools, APIs, and data sources to enhance data collection efficiency.
- Team Leadership: Build and mentor a team of GIS specialists, automation engineers, and data experts to support process automation initiatives.
- Experience: 5-7+ years of experience in technical project management, process optimization, or automation within data-intensive environments.
- Data Workflow Expertise: Strong understanding of large-scale data workflows, data ingestion, and process optimization.
- Leadership Skills: Proven experience in leading cross-functional teams and managing stakeholders across engineering and business units.
- GIS Experience: Prior experience in GIS, geospatial data processing, or location-based services.
- Programming Background: Basic programming background (Python, SQL, or scripting languages) for process automation.
- Big Data Technologies: Experience working with big data technologies (PostGIS, Snowflake, DuckDB, or similar).
The successful candidate will work closely with the Head of GIS to establish process improvements, scalability strategies, and cost-effective solutions for handling large geospatial datasets. They will ensure that all geospatial data workflows comply with industry standards, regulations, and best practices.
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