Regrid is shaping location intelligence with the first-ever 100% nationwide land parcel data coverage map.

Our customers can work with the data, create beautiful maps & surveys or license it for use in their own maps, apps and databases.

We are based in Detroit with colleagues and collaborators in cities across the country.

DATA ANALYST I OR II (PROCESSING)

Full-time, 100% remote, open to U.S. candidates only

Reporting to the Geographical Data Manager, you will support the data team in producing a high-quality, nationwide spatial dataset.

Regrid maintains a geospatial dataset of over 158 million parcel polygons, plus rich associated information, all collected from thousands of sources. The core of this role will involve extract, transform, load (ETL) work organized around a repeating 2-week cycle: ingesting new data, transforming it into our schema, cleaning it to meet our standards, and packing it for deployment to our clients. We primarily work with open source geospatial tools like PostGIS, GDAL (ogr2ogr), and QGIS.

Side projects can range from identifying and fixing a specific problem in one city to writing tools to analyze millions of spatial records. Your contributions will be a necessary part of improving the efficiency and quality of our data and processes.

We recognize that individuals from marginalized and underrepresented backgrounds are less likely to apply for positions if they do not meet 100% of the job requirements. If you meet the majority of the listed duties and requirements, we encourage you to apply.

Key Responsibilities

• Data processing (70-80%)
• Write ETL configurations to import, clean and process a varied and complex set of spatial and tabular data
• Identify and solve problems in the data and data pipeline
• Work with QC analysts to ensure data is reviewed and accurate
• Investigate and analyze new datasets from public sources and vendors for inclusion in our products
• Data analysis (20-30%)
• With the team, identify structural problems, pipeline bottlenecks, and places to improve process
• Implement dataset-wide fixes and improvements
• Report on attributes of the data
• Support our sales and product teams by analyzing data to answer client and prospect questions
• Investigate issues reported by data clients
• Use Ruby and other scripting tools to build utilities to clean & manage data
• Work on projects that showcase our data, such as maps, visualizations, or small demos
• Assist with data classification

Job Requirements

• The ability to rapidly and efficiently synthesize a diverse set of data
• Attention to detail and the ability to find patterns and problems in complex information
• Experience writing Postgres SQL queries, including joins and indexes; basic spatial queries (eg spatial intersection), familiarity with database connections and a database client
• Experience with open-source spatial tools like PostGIS, QGIS, and GDAL (ogr2ogr), tabular data (Excel and CSV), and common spatial formats (eg Shapefiles, GeoJSON)
• An inquisitive mind and desire to learn data tools and techniques
• Experience with git and github or gitlab
• Ability to work comfortably at the command line, including basic operations like changing directories, listing files, and inspecting files with tools like cat, head, and tail

Bonus Points

We’d love to know if you have experience with any of the following, but please don’t count yourself out if you don’t:

• Experience working with open and public datasets, property data, or other land-related spatial data.
• Experience with the Unix philosophy and standard unix/linux utilities, including sed, awk, grep, and parallel
• Basic or better scripting skills in at least one programming language like Python, Ruby, or Javascript (Node.js). Familiarity with programming concepts including variables, loops, hashes (dictionaries), arrays, and reading files. At Regrid, we primarily use Ruby and Javascript.
• A portfolio of data-focused projects you’ve contributed to, and/or code published on github or elsewhere.
• Experience with the Esri ecosystem
• Experience with the Mapbox ecosystem