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Senior Geospatial Data Engineer Jobs in Atlanta, GA

Cushman & Wakefield

Junior Data Scientist

Atlanta, GA · On-site

... senior stakeholders, producing clean, well-documented, and reproducible outputs. Data Engineering ... Working knowledge of geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or ...

Cushman & Wakefield

Junior Data Scientist

Atlanta, GA · On-site

... senior stakeholders, producing clean, well-documented, and reproducible outputs. Data Engineering ... Working knowledge of geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or ...

Cushman & Wakefield

Junior Data Scientist

Atlanta, GA · On-site

... senior stakeholders, producing clean, well-documented, and reproducible outputs. Data Engineering ... Working knowledge of geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or ...

Cushman & Wakefield

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Works closely with senior economists, analytics leads, and technical teams to deliver high-quality ... Partner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real ...

Cushman & Wakefield

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Works closely with senior economists, analytics leads, and technical teams to deliver high-quality ... Partner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real ...

Cushman & Wakefield

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Works closely with senior economists, analytics leads, and technical teams to deliver high-quality ... Partner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real ...

Cushman & Wakefield

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Works closely with senior economists, analytics leads, and technical teams to deliver high-quality ... Partner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real ...

Hiscox

Senior Data Engineer

Atlanta, GA · On-site

$160K - $170K/yr

Permanent Build a brilliant future with Hiscox Senior Data Engineer (Hiscox Inc., Atlanta, GA) * Serve as a core and professional member of our Data Engineering practice to build and operationalize ...

New

Paul Hastings

Senior Data Engineer

Atlanta, GA · On-site

$194K/yr

Job Title Senior Data Engineer Location Atlanta, Boston, Charlotte, Chicago, Dallas, Houston, Los Angeles, New York Regular/Temporary Regular Summary We have an opening for a Senior Data Engineer.

Caresoft Inc.

Sr. Data Engineer

Atlanta, GA · On-site

$62 - $66/hr

Title: Sr. Data Engineer Location: Atlanta, Georgia 30334(Hybrid) Durartion: Long Term Skills: Bachelor's degree in computer science, Information Systems, or related field. Years of experience in ...

System One

Senior Data Engineer

Atlanta, GA · On-site

$147K/yr

Senior Data Engineer Location: Preference will be given to candidates located in Atlanta, GA or the D.C. Metro area. US Citizen or Legal Permanent Resident required per government contract Clearance:

System One

Senior Data Engineer

Atlanta, GA · On-site

$147K/yr

Senior Data Engineer Location: Preference will be given to candidates located in Atlanta, GA or the D.C. Metro area. US Citizen or Legal Permanent Resident required per government contract Clearance:

System One

Senior Data Engineer

Atlanta, GA · On-site

$147K/yr

Senior Data Engineer Location: Preference will be given to candidates located in Atlanta, GA or the D.C. Metro area. US Citizen or Legal Permanent Resident required per government contract Clearance:

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All JobsGeospatial Data Engineer JobsSenior Geospatial Data Engineer JobsSenior Geospatial Data Engineer Jobs in Atlanta, GA

Senior Geospatial Data Engineer information

See Atlanta, GA salary details

$77.9K

$121.5K

$168.3K

How much do senior geospatial data engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for senior geospatial data engineer in Atlanta, GA is $121,485.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,900.00 and $138,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a senior geospatial data engineer?

To thrive as a Senior Geospatial Data Engineer, you need advanced expertise in geospatial analysis, spatial databases, and programming languages like Python or SQL, often backed by a degree in GIS, computer science, or related fields. Familiarity with GIS platforms (such as ArcGIS or QGIS), cloud computing services, and big data frameworks is typically required, along with relevant certifications in GIS or cloud technologies. Strong problem-solving, communication, and project leadership skills set top performers apart in this role. These competencies are essential for designing and implementing scalable geospatial solutions that accurately support decision-making and organizational goals.

What is the difference between Senior Geospatial Data Engineer vs Geospatial Data Analyst?

AspectSenior Geospatial Data EngineerGeospatial Data Analyst
CredentialsBachelor's or Master's in GIS, Computer Science, or related field; experience with GIS software and programmingBachelor's or Master's in Geography, GIS, or related field; proficiency in GIS tools and data analysis
Work EnvironmentData engineering teams, GIS departments, tech companies, government agenciesResearch teams, GIS departments, consulting firms, government agencies
Employer & Industry UsageTech firms, environmental agencies, urban planning, transportationResearch institutions, government agencies, consulting firms

The Senior Geospatial Data Engineer focuses on building and maintaining geospatial data infrastructure, pipelines, and systems, often requiring programming and data engineering skills. In contrast, the Geospatial Data Analyst primarily interprets and visualizes geospatial data to support decision-making. Both roles require GIS knowledge but differ in technical depth and focus areas.

What are some typical challenges a senior geospatial data engineer faces when integrating diverse data sources?

One common challenge is ensuring data compatibility and consistency across various formats, such as raster, vector, and tabular data, which often originate from different providers or systems. Senior Geospatial Data Engineers must address issues like differing coordinate reference systems, data quality, and incomplete metadata. Collaborating closely with data scientists, GIS analysts, and software developers is crucial to develop robust pipelines and resolve integration issues efficiently. Staying updated with evolving geospatial technologies and standards also plays a key role in overcoming these challenges.

What is a senior geospatial data engineer?

A Senior Geospatial Data Engineer is a specialized data professional who designs, develops, and maintains systems that process and analyze spatial or geographic data. They work with large geospatial datasets, build data pipelines, and develop scalable solutions for mapping, location intelligence, and spatial analytics. These engineers often collaborate with data scientists, GIS specialists, and software developers to integrate geospatial data into applications and decision-making processes. Their expertise includes working with GIS software, spatial databases, and cloud-based geospatial tools. Senior-level engineers typically also mentor junior staff and help set technical direction for geospatial projects.
What are the most commonly searched types of Geospatial Data Engineer jobs in Atlanta, GA? The most popular types of Geospatial Data Engineer jobs in Atlanta, GA are:
Senior Geospatial Data Engineer jobs near you
Infographic showing various Senior Geospatial Data Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $121,485 per year, or $58.4 per hour.

Senior Data Engineer

Intercontinental Exchange Holdings, Inc.

Atlanta, GA • On-site

$101K - $138K/yr

Full-time

Re-posted 25 days ago

Job description

Overview
Job Purpose
ICE Data Services (an Intercontinental Exchange company) is seeking a Senior Data Engineer to join its Data Impact & Innovation team. This team supports a variety of reference data, index, climate finance, and alternative data products. The role contributes to the data platforms and pipelines that help the financial sector understand and respond to carbon transition risk, physical risk, and related challenges.
Our team maintains a global-scale geospatial data platform in Google BigQuery, holding many terabytes of data across carbon transition risk, physical climate risk, and social/demographic features - feeding analytical products for fixed income and real estate financial instruments, supporting the ambitious product roadmap for ICE Climate and other data products. Our engineering stack includes:
  • Orchestration: Airflow, moving toward composable task abstractions over a shared pipeline framework
  • Transformation: dbt, and other data lineage and DQA tools, primarily using Google BigQuery
  • Geospatial processing: Python (GeoPandas, Shapely, GeoAlchemy2 against PostGIS) for vector operations, and R
  • Execution and compute environments: Hybrid across Google Cloud Platform and on-premise RHEL Linux infrastructure
  • Ingestion: Third-party vendor feeds via API, SFTP, cloud storage, and database replication

Typical engineering challenges include working with data science and climate science teams in operationalizing trained models and data pipelines, absorbing upstream vendor corrections and historical restatements without corrupting downstream artifacts, scaling raster x vector joins at terabyte scale, evolving schemas and spatial-indexing strategies as data sources broaden, and balancing long-running batch workflows against emerging sub-daily refresh cadences.
Responsibilities
  • Take significant components of the data platform from "works" to "mature" - tightening reliability, observability, cost/performance characteristics, and operational discipline across our ingestion, transformation, and serving layers.
  • Establish and foster adoption of technical standards for the team's work - including Airflow DAG structure, dbt model layout, BigQuery schema and partitioning conventions, pipeline testing practices, and deployment workflows.
  • Lead technical design discussions, mentor other data engineers through code review, pairing, and design-doc review, and grow them along their career path.
  • Act as a technical point of contact for cross-functional initiatives - partnering with data science, climate science, product, and infrastructure colleagues to drive forward decisions and make tradeoffs explicit.
  • Deliver day-to-day work across the stack above - authoring Airflow DAGs and dbt models, contributing geospatial processing capabilities, and shipping cleanly partitioned, audit-friendly outputs from ingestion through serving.
  • Support data science and climate science teams by helping design the tooling, training, and validation environments, and by deploying their trained models into production.
  • Effectively leverage AI and LLM-based developer tooling to accelerate development workflows and improve code quality.
  • Identify opportunities to improve and optimize data pipelines - for speed, cost, robustness, integrity, and operational simplicity.
  • Work with business analysts, product management, and adjacent engineering teams to understand and refine new data requirements.

Knowledge and Experience
  • 5+ years of professional experience as a data engineer, with a track record of architecting, shipping, and operating production data pipelines end-to-end.
  • Experience mentoring and developing other data engineers - through code review, pairing, design discussions, and career coaching.
  • Ability to establish and foster adoption of technical standards.
  • A habit of actively monitoring, evaluating, and prototyping emerging big-data, geospatial, and machine-learning technologies and platforms - staying conversant in advances across cloud data engines, geospatial libraries and standards, and ML/MLOps frameworks - and bringing the most promising into the team's design discussions, evaluations, and adoption decisions.
  • Strong system-design judgment across the tradeoff space of performance, cost, maintainability, and auditability
  • Comfort scoping, decomposing, and delegating work for other engineers.
  • Strong written and verbal communication - able to translate technical tradeoffs for senior business, product, and client stakeholders.
  • Deep fluency in modern, typed Python as a primary working language, including comfort with type-driven design (e.g. Pydantic v2).
  • Strong SQL background, including experience partitioning, clustering, and performance-tuning queries on modern cloud warehouses - Google BigQuery experience strongly preferred.
  • Production experience with dbt for managing warehouse transformations, and with Airflow (or a comparable orchestrator) for workflow orchestration.
  • Solid grounding in geospatial data engineering - Python tooling (GeoPandas, Shapely), spatial databases (PostGIS), raster processing, or adjacent skills.
  • A systems-thinking orientation: anticipates cascading effects of upstream data changes, schema evolution, and vendor corrections; designs pipelines with observability, auditability, and graceful failure in mind.
  • Comfort owning production incidents and debugging distributed systems.
  • Experience working cooperatively with systems, network, and infrastructure engineering and operations teams to ensure proper monitoring, alerting, and incident response workflows.
  • Demonstrated ability to integrate AI/LLM coding assistants productively - treating them as a force multiplier rather than a substitute for judgment.
  • Curiosity about the financial and climate/geospatial domains and contexts the team operates in.

Preferred Knowledge and Experience
  • Well-versed in and opinionated about the modern Python ecosystem.
  • Exposure to columnar and lakehouse technologies (Parquet, ClickHouse, DuckDB).
  • Working understanding of data lineage, data quality validation, and metadata/cataloging frameworks.
  • Prior experience in a hybrid cloud + on-premise environment, and with full software development lifecycle (SDLC) best practices and processes.
  • Prior exposure to ML deployment workflows - supporting data science teams with training tooling and/or model-serving infrastructure.
  • Familiarity with R, particularly geospatial packages.

#LI-HR1 #LI-ONSITE
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Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.

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