GCP Data Engineer

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

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. #J-18808-Ljbffr Pacer Group