Job Title: GCP Data Engineer (Geospatial Senior Analyst)
Location: Austin, TX (Preferred) OR Remaining Client Locations / Remote
Work Arrangement: Hybrid (Austin, TX) or 100% Remote Eligible
Employment Type: Contract
Duration: 6 months (Based on July 1, 2026 – December 31, 2026 timeline)
Pay Range: $40.00/hr. to $42.00/hr. on W2 | $55.00/hr. to $56.00/hr. on C2C
Domain: Healthcare / Health Tech Analytics
Application Deadline: June 20, 2026
SKILLS REQUIRED:
Primary (Must-Have):
�6 to 10 years of data engineering experience with a heavy specialization in geospatial processing
�Advanced hands-on proficiency in GCP Dataflow, designing both streaming and batch pipelines for spatial and temporal datasets
�Deep expertise in GCP BigQuery, including data modeling, geospatial functions (GIS), and high-scale query optimization (partitioning/clustering)
�Proven knowledge of Apache Kafka architectures, including topic design, consumer group configurations, and real-time event streaming
�Strong Python 3 programming capabilities to build modular, testable, and reusable spatial automation scripts
�Practical experience using PySpark to clean, enrich, and transform large-scale distributed datasets
Secondary (Good to Have):
�Solid working knowledge of core geospatial mechanics: coordinate systems, spatial joins, and map projections
�Experience with cloud optimization, resource allocation monitoring, and cost-efficient storage architecture design
�Background building automated data quality gates, validation checks, and reproducible pipeline unit tests
�Clear technical communication skills with a track record of collaborating with cross-functional product owners and data consumers
POSITION OVERVIEW
We are seeking a Senior GCP Data Engineer / Geospatial Analyst with 6 to 10 years of specialized experience to design, build, and optimize high-throughput geospatial data pipelines. Operating in a flexible remote or hybrid capacity out of Austin, TX, this role focuses on supporting map-based analytics, geospatial positioning systems, and location-aware digital products. The ideal candidate will combine rigorous cloud data engineering practices (GCP, Kafka, PySpark) with advanced spatial analysis techniques to process complex real-time location events, sensor feeds, and temporal datasets into highly actionable business intelligence.
ROLES & RESPONSIBILITIES
�Design, deploy, and maintain robust geospatial data ingestion pipelines using GCP Dataflow to reliably process high-volume, real-time spatial records.
�Develop and optimize complex analytical queries in GCP BigQuery, converting raw geographic telemetry into highly curated tables, analytical models, and dashboards.
�Architect and manage Apache Kafka event streams to capture real-time location feeds, tracking systems, and sensor movements with minimal processing lag.
�Implement highly scalable PySpark data transformation matrices to clean, isolate anomalies from, and aggregate massive spatial datasets.
�Author enterprise-grade Python 3 scripts to automate complex data workflows, orchestrate cron-based data jobs, and deliver repeatable analytical insights to stakeholders.
�Tune and structure BigQuery data lakes by defining optimized schema clustering, geometric data indexing, and temporal partitioning strategies for multi-terabyte datasets.
�Support incident mitigation workflows, performing deep-dive root-cause investigations on pipeline performance drops or spatial data degradation, and engineering permanent programmatic fixes.
BENEFITS
Medical | Dental | Vision | 401(k)
EEOC Compliance
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.
DISCLAIMER
AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.