Top 12 GIS Manager Skills to Put on Your Resume
In the rapidly changing world of Geographic Information Systems (GIS), standing out as a GIS Manager means blending deep technical know-how with crisp leadership. Your resume should signal you can steer teams, wrangle complex spatial data, and turn maps into decisions. Pack it with the skills that actually move the needle, and you’ll look ready to run major GIS initiatives anywhere.
GIS Manager Skills
1. ArcGIS
ArcGIS is a comprehensive platform for creating, managing, analyzing, and sharing spatial data and maps. It underpins enterprise GIS—desktop, web, mobile, and services—so decisions aren’t guesswork.
Why It's Important
For a GIS Manager, ArcGIS ties together analysis, data governance, and delivery. You get a single ecosystem for authoritative data, clear workflows, and secure sharing. Less friction, more insight.
How to Improve ArcGIS Skills
Focus on the pieces that compound:
Move fully to ArcGIS Pro: ArcMap is retired; Pro is the primary desktop. Standardize projects, toolboxes, and models there.
Strengthen automation: Use ArcPy and the ArcGIS Python API to script data refreshes, publishing, and QA. Kill repetitive tasks.
Harden data quality: Stand up data rules, attribute rules, and validation workflows (including Data Reviewer) to keep errors from spreading.
Use ArcGIS Online and Enterprise intentionally: Separate staging vs production. Control sharing. Leverage web maps/apps for quick wins.
Integrate across the stack: Connect to enterprise systems (work orders, assets, CRM). Treat GIS as a service, not a silo.
Invest in skills: Regular training, playbooks, and brown-bag demos. Rotate responsibilities so knowledge sticks across the team.
Governance and monitoring: Track services, usage, and performance. Archive what’s stale, scale what’s used.
Do these well and the platform hums—fewer outages, faster delivery, cleaner data.
How to Display ArcGIS Skills on Your Resume
2. QGIS
QGIS is a powerful open-source GIS used for analysis, cartography, and data management. It speaks many formats, extends with plugins, and thrives in mixed environments.
Why It's Important
It’s cost-effective, flexible, and richly capable. Perfect for teams that need control, transparency, and the freedom to tailor workflows.
How to Improve QGIS Skills
Lift both capability and reliability:
Track stable releases: Standardize on the current Long Term Release for production; pilot new features separately.
Curate plugins: Approve a known set. Audit periodically. Fewer plugins, fewer surprises.
Use Processing and Model Builder: Chain tools, parameterize tasks, and document steps so anyone can run them.
Lean into PyQGIS: Script imports, transformations, and cartography. Keep a shared snippet library.
Modern data formats: Prefer GeoPackage and Parquet for portability and speed. Centralize styles and symbols.
QGIS Server and web: When needed, deploy lightweight OGC services or pair with existing web stacks.
Standards and training: Style guides, CRS conventions, folder structure, and routine refreshers.
Small guardrails go a long way toward stability and speed.
How to Display QGIS Skills on Your Resume
3. Python
Python is the backbone of modern GIS automation and analysis—cleaning data, crunching vectors and rasters, and wiring systems together.
Why It's Important
It unlocks repeatability. Complex geoprocessing pipelines become scripts and services. Less manual clicking, more consistent outcomes.
How to Improve Python Skills
Aim for practical fluency:
Master the basics: Functions, classes, packaging, virtual environments. Use conda/mamba to manage geospatial stacks cleanly.
Use core geo libraries: GeoPandas, Shapely, pyproj, rtree, Fiona or pyogrio for I/O; Rasterio, rioxarray, and xarray for rasters; OGR/GDAL when needed.
Automate at scale: ArcPy and ArcGIS Python API for Esri stacks; psycopg2/SQLAlchemy for databases; airflow or simple schedulers for jobs.
Performance habits: Vectorize, batch operations, use spatial indexes, chunk rasters. Profile first, optimize second.
Quality and reliability: Tests, logging, type hints, and clear docstrings. Notebooks for exploration; packages for production.
Data discovery and cloud: Work with STAC catalogs, cloud-optimized GeoTIFFs, object storage. Stream, don’t always download.
Build a small portfolio of repeatable workflows. Show impact—time saved, errors avoided, insights delivered.
How to Display Python Skills on Your Resume
4. SQL
SQL is the language of data. In GIS, it powers queries that slice, filter, join, and measure across massive spatial and non-spatial tables.
Why It's Important
Because fast, correct queries mean faster maps, clearer analysis, and leaner pipelines. It’s the difference between minutes and milliseconds.
How to Improve SQL Skills
Think both fundamentals and spatial depth:
Nail the core: SELECT, WHERE, JOIN, GROUP BY, window functions, CTEs. Read query plans until they’re second nature.
Spatial SQL: ST_Intersects, ST_Contains, ST_DWithin, ST_Distance, ST_Centroid, ST_Simplify, ST_SnapToGrid. Know when each shines.
Indexing: Create and maintain B-tree for attributes, GiST/SP-GiST for geometry/geography. Keep stats fresh.
Optimization: Use EXPLAIN ANALYZE, reduce row counts early, avoid SELECT *. Materialize when it pays off.
Scale patterns: Partition big tables, schedule maintenance, apply constraints, manage roles and permissions.
Apply in tools: Run SQL inside your GIS platform and in the database directly. Same logic, different surfaces.
Make performance visible—dashboards, slow-query logs, before/after timings.
How to Display SQL Skills on Your Resume
5. JavaScript
JavaScript drives interactive, web-based maps. Pan, click, filter, animate—right in the browser.
Why It's Important
It’s how users experience GIS today. From internal dashboards to public apps, JavaScript is the front door to your data.
How to Improve JavaScript Skills
Make your maps feel effortless:
Ground yourself in the language: Scope, async/await, modules, array methods. Then add TypeScript where it helps.
Pick the right mapping libs: Leaflet for lightweight 2D, OpenLayers for advanced OGC and projections, MapLibre GL for WebGL vector tiles. ArcGIS Maps SDK for JS if you’re deep in the Esri stack. deck.gl for heavy-duty visualization.
Modern tooling: Use a bundler, linting, formatting, and environment configs. Keep bundles slim.
Performance: Prefer vector tiles, server-side filtering, and clustering. Render less, not more.
UX and accessibility: Keyboard navigation, focus states, high-contrast palettes, touch gestures that feel natural.
Maintainability: Components, clear state management, and shared utilities for popups, legends, and layers.
Ship small, iterate fast, measure what users do—not just what you think they do.
How to Display JavaScript Skills on Your Resume
6. Remote Sensing
Remote sensing collects information from afar—satellites, aircraft, drones, even ground sensors. Multispectral, hyperspectral, SAR. Big, rich, continuous.
Why It's Important
It brings timeliness. Coverage. Consistency. Perfect for monitoring change, mapping at scale, and filling blind spots between surveys.
How to Improve Remote Sensing Skills
Sharpen the pipeline end to end:
Get better inputs: Use appropriate spatial, spectral, and temporal resolution. Landsat 9, Sentinel-1/2, and commercial imagery when the use case demands it.
Preprocess well: Atmospheric correction, cloud and shadow masking, radiometric calibration, co-registration. Clean in, clean out.
Analysis at scale: Apply ML for classification and change detection. Use tiled rasters, chunked processing, and COGs to stay fast.
Diverse sources: Blend satellite, UAV, lidar, and ground truth. Fuse rasters with vector context to target action.
Standards and catalogs: Organize with STAC-like metadata. Document lineage, dates, sensors, and processing steps.
Upskill the team: Short courses, internal playbooks, and peer reviews. Reuse notebooks and models across projects.
When the workflow is tight, updates become routine, not heroic.
How to Display Remote Sensing Skills on Your Resume
7. AutoCAD
AutoCAD creates precise 2D/3D drawings. In GIS work, it often bridges design files and spatial databases.
Why It's Important
Design data lives in DWG/DGN. Bringing it into GIS, cleanly and accurately, keeps engineering and mapping in sync.
How to Improve AutoCAD Skills
Make CAD-to-GIS smooth, not brittle:
Use the right toolset: AutoCAD Map 3D or Civil 3D for CRS handling, FDO connections, and direct read/write of spatial formats.
Standardize layers and blocks: Layer naming, object data, and attribute extraction rules. Less guesswork during conversion.
Coordinate systems first: Assign and verify CRS before exchange. Avoid shifting surprises later.
Automate repeats: Scripts/LISP for cleaning layers, exploding blocks when needed, and exporting with consistent schemas.
QA every hop: Geometry validation, topology checks, and attribute completeness before loading into the geodatabase.
Tidy CAD in, reliable GIS out.
How to Display AutoCAD Skills on Your Resume
8. PostgreSQL/PostGIS
PostgreSQL is a robust open-source relational database. PostGIS adds spatial types and functions, turning it into a powerhouse for storing and querying geodata.
Why It's Important
It centralizes your spatial data with speed and integrity. Complex analytics run in-database, services read directly, and everyone uses the same source of truth.
How to Improve PostgreSQL/PostGIS Skills
Performance and reliability are a practice, not an accident:
Index smartly: GiST/SP-GiST for geometry/geography, and composite indexes for common filters. Reindex when fragmentation bites.
Partition big tables: Range or list partitions by region or date. Keep maintenance and queries snappy.
Tune configuration: Calibrate work_mem, shared_buffers, effective_cache_size, maintenance_work_mem to your hardware and workload.
Maintain diligently: VACUUM (including auto-vacuum tuning), ANALYZE, and frequent statistics updates. Monitor bloat.
Optimize queries: Use EXPLAIN ANALYZE, reduce geometry complexity where possible (ST_Simplify, ST_SnapToGrid), and push filters before joins.
Spatial functions wisely: Leverage ST_Tile/tiling patterns for rasters, ST_AsMVT for vector tiles, and appropriate distance operators.
Pool connections: Add a connection pooler to handle bursts and microservices cleanly.
Monitor and alert: Track slow queries, locks, I/O, and cache hit ratios. Fix hot spots early.
Upgrade regularly: New PostgreSQL and PostGIS releases bring planner improvements and spatial features worth having.
Backups and roles: Enforce least-privilege access, test restores, and script migrations. No heroics on cutover day.
A healthy database makes every downstream tool look better.
How to Display PostgreSQL/PostGIS Skills on Your Resume
9. R
R is a language and ecosystem for statistics, visualization, and spatial analysis. Especially handy when your questions are analytical and your answers need proof.
Why It's Important
It pairs spatial data with serious stats. Reproducible reports, models you can defend, maps that tell the story cleanly.
How to Improve R Skills
Lean into modern spatial R:
Use the right packages: sf for vectors, terra (successor to raster) for rasters, stars for large multidimensional data, exactextractr for summarized overlays.
Workflow discipline: R Markdown or Quarto for reports, renv for dependency management, targets or drake for pipelines.
Visualization: tmap and ggplot2 for cartography and analysis graphics; leaflet for interactive maps.
Performance: Chunk big rasters, write intermediates, and parallelize where sensible.
Bridge to databases and Python: DBI/duckdb/PostgreSQL connections; reticulate if a Python tool is best for a step.
Teach and share: Internal notebooks, examples with small sample data, and a package of common helpers.
Clarity beats cleverness. Favor readable, reproducible analysis.
How to Display R Skills on Your Resume
10. FME
FME (Feature Manipulation Engine) is a no-code/low-code platform for transforming and moving spatial and tabular data across systems. Automation without reinventing the wheel.
Why It's Important
It standardizes “messy in, tidy out.” Massive time-saver for ETL, data validation, and system-to-system handshakes.
How to Improve FME Skills
Turn it into a reliable factory:
Know the lineup: Use FME Form for building workflows; FME Flow (and Flow Hosted) for scheduling, scaling, and APIs.
Template everything: Naming, logging, error handling, and notifications. Make every workspace self-diagnosing.
Parallelism and performance: Readers/writers tuned, transformers minimized, feature caching strategic, and engines scaled for bursts.
Data model discipline: Clean schemas in, clean schemas out. Validate early; map fields explicitly.
Version control: Keep workspaces in source control, review changes, and tag releases.
Monitor and iterate: Dashboards for run times and failures. Fix the top offenders first.
Upskill the team: Short courses, internal clinics, and a shared catalog of reusable components.
Automations should be boring—in the best way.
How to Display FME Skills on Your Resume
11. CARTO
CARTO (formerly CartoDB) is a cloud-native platform for analyzing and visualizing location data, increasingly tied to data warehouses and scalable SQL analytics.
Why It's Important
It lets teams build interactive maps fast, share insights widely, and push heavy lifting into cloud data platforms. Speed to value matters.
How to Improve CARTO Skills
Get more from the platform:
Clean inputs: Structure datasets, document fields, and define join keys. Garbage in still equals garbage out.
Lean on SQL and spatial functions: Write clear queries; push aggregations and geoprocessing to the warehouse when available.
Tailored visuals: Use Builder smartly, style with purpose, and keep legends and popups crisp.
Automate refreshes: Scheduled data pulls, incremental updates, and parameterized workflows.
Performance basics: Index large tables upstream, prefer vector tiles, and paginate results in apps.
Collaboration and governance: Roles, shared workspaces, and publishing standards. Know what’s authoritative.
Stay current: Track new features like analytics toolboxes and warehouse connectors. Train the team when they land.
Security: Respect access controls and data privacy. Mask sensitive attributes where needed.
Simple, fast, and clear beats flashy and slow every time.
How to Display CartoDB Skills on Your Resume
12. Leaflet
Leaflet is a lightweight JavaScript library for interactive maps. Minimal footprint, wide plugin ecosystem, quick to learn.
Why It's Important
When you need fast, responsive web maps without heavy frameworks, Leaflet punches above its weight.
How to Improve Leaflet Skills
Squeeze more out of it:
Pick plugins carefully: Drawing, geocoding, heatmaps, clustering—add only what you need. Fewer dependencies, fewer woes.
Handle scale: Use vector tiles or server-side filtering. Cluster dense points. Prefer Canvas rendering for huge layers.
Interaction polish: Intuitive gestures, fit-to-extent buttons, and concise popups. Good defaults feel magical.
Accessibility: Keyboard support, labeled controls, and high-contrast basemaps. Make it usable for everyone.
Mobile readiness: Touch targets big enough, performant redraws, and sensible offline fallbacks when possible.
Keep it maintainable: Small components, consistent layer management, and centralized style rules.
If it loads fast and feels smooth, users stay.
How to Display Leaflet Skills on Your Resume
