Geospatial Data Architect

CenterPoint Energy • Houston, TX

3d

About The Position

CenterPoint Energy and its predecessor companies have been in business for more than 150 years.

Our Vision: Our vision is to become the most admired utility in the United States through the execution of our long-term growth strategy. We have an unwavering commitment to safely and reliably deliver electricity and natural gas to millions of people.

Our Commitment: CenterPoint Energy is committed to creating an inclusive work environment where business results are achieved through the skills, abilities and talents of our diverse workforce.
At CenterPoint Energy, individuals are respected for their contributions toward our company objectives. We strive for an inclusive work environment across all levels that is reflective of the available workforce in the communities we serve.
SUMMARY:The Geospatial Architect serves as an enterprise leader responsible for designing and governing CenterPoint Energy’s geospatial data architecture, cloud‑based spatial analytics platforms, and spatial‑enabled data products. This role focuses on scalable data pipelines, cloud geospatial processing, advanced analytics, and enterprise integration. The position works closely with the GIS team to ensure alignment between operational geospatial systems and enterprise data and analytics platforms, supporting business units, engineering, planning, AI/ML, and system reliability initiatives.ESSENTIAL FUNCTIONSArchitect cloud native geospatial data ecosystems using BigQuery GIS, Dataflow, and scalable storage formats (Parquet/GeoParquet,etc.).•
Design spatial data models, schemas, indexing strategies, and governance standards optimized for analytics, AI/ML, and reporting.•
Translate business and operational requirements into data architecture specifications, collaborating with GIS to align operational datasets with analytical models.•
Establish patterns for data ingestion, versioning, lineage, enrichment, and consumption across analytics tools.•
Lead development of automated spatial ETL/ELT pipelines using Python, SQL, and event driven architectures.•
Ensure data quality via geometry validation, topology checks, schema enforcement, and automated testing.•
Integrate operational GIS datasets into analytical and cloud platforms with clear metadata and lineage.•
Architect cloud geospatial platforms on GCP, including BigQuery, Cloud Run, Cloud Storage, and VPC/Security.•
Implement Infrastructure as Code for geospatial systems (Terraform, Cloud Build). •
Collaborate with AI/ML teams to enable spatial features and model ready datasets. •
Scale emerging cloud geospatial capabilities such as vector tiles, quadtrees, and semantic spatial search.•
Act as the primary geospatial architecture expert within Data & Analytics.•
Define the enterprise geospatial data roadmap aligned with corporate strategy.•
Mentor data engineers, analysts, and architects on spatial and cloud architecture.EDUCATIONRequires a bachelor’s degree in GIS, Computer Science, Engineering, Data Science, or related field

Requirements

• 12+ years of progressive experience in geospatial data engineering, cloud architecture, or analytics‑oriented GIS roles.
• Proficiency with SQL, BigQuery GIS or PostGIS, Python spatial libraries, or similar technologies.
• Experience building production ETL/ELT pipelines and spatial analytics workflows.
• Proven expertise in Python, with hands-on experience using machine learning libraries such as scikit-learn, TensorFlow, PyTorch, and JAX.
• Extensive experience with cloud services such as, including Vertex AI, BigQuery, Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, and Cloud Run.
• Deep proficiency in data pipeline orchestration, streaming architectures, and containerization using Docker, Kubernetes, and serverless frameworks.
• Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or Deployment Manager.
• Demonstrated success in leading high-performing, cross-functional technical teams, mentoring junior engineers, and fostering a culture of innovation.

Nice To Haves

• MBA or advanced degree in mathematics, GIS, business, finance, statistics, computer science, or a related field.
• Certifications in relevant cloud platforms (e.g., Google Cloud Certified – Professional Data Engineer, Professional Cloud Architect).
• Strong understanding of cloud networking (e.g., DNS, load balancing, VPCs, NAT, peering) and zero-trust security architectures.
• Familiarity with MLOps and LLMOps practices, including CI/CD for ML, model registry, and automated retraining pipelines.
• Proficiency in JSON-based messaging, API integration patterns, and event-driven architectures.
• Experience with vector databases, semantic search, and generative AI architectures.
• Experience with data governance platforms (e.g., Collibra, Atlan) and metadata management.
• Full stack development experience using technologies such as React, Flask, Node.js, Firestore, and GraphQL.

Responsibilities

• Architect cloud native geospatial data ecosystems using BigQuery GIS, Dataflow, and scalable storage formats (Parquet/GeoParquet,etc.).
• Design spatial data models, schemas, indexing strategies, and governance standards optimized for analytics, AI/ML, and reporting.
• Translate business and operational requirements into data architecture specifications, collaborating with GIS to align operational datasets with analytical models.
• Establish patterns for data ingestion, versioning, lineage, enrichment, and consumption across analytics tools.
• Lead development of automated spatial ETL/ELT pipelines using Python, SQL, and event driven architectures.
• Ensure data quality via geometry validation, topology checks, schema enforcement, and automated testing.
• Integrate operational GIS datasets into analytical and cloud platforms with clear metadata and lineage.
• Architect cloud geospatial platforms on GCP, including BigQuery, Cloud Run, Cloud Storage, and VPC/Security.
• Implement Infrastructure as Code for geospatial systems (Terraform, Cloud Build).
• Collaborate with AI/ML teams to enable spatial features and model ready datasets.
• Scale emerging cloud geospatial capabilities such as vector tiles, quadtrees, and semantic spatial search.
• Act as the primary geospatial architecture expert within Data & Analytics.
• Define the enterprise geospatial data roadmap aligned with corporate strategy.
• Mentor data engineers, analysts, and architects on spatial and cloud architecture.

Benefits

• Competitive pay
• Paid training
• Benefits eligibility begins on your first day
• Transit subsidies
• Flexible work schedule, paid holidays and paid time off
• Access to discounts at fitness clubs and an on-site wellness center at our headquarters in Houston
• Professional growth and development programs including tuition reimbursement
• 401(k) Savings Plan featuring a company match dollar-for-dollar up to 6% and a company contribution of 3% regardless of your contribution

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level