GCP DATA ENGINEER
Contract • Denver, Colorado • On-site / Hybrid
6–12 Months (with extension potential)
Denver, Colorado —5 days on-site
Technology / Data Engineering
POSITION OVERVIEW
We are seeking an experienced GCP Data Engineer to join our team on a contract basis in Denver, Colorado. The ideal candidate will have deep expertise in Google Cloud Platform services, Java-based pipeline development, and enterprise ETL frameworks. You will design and implement scalable data pipelines, work with large distributed datasets, and collaborate with cross-functional teams to deliver high-quality data solutions.
KEY RESPONSIBILITIES
- Design, develop, and maintain robust ETL/ELT pipelines on Google Cloud Platform using Java and cloud-native services
- Build and optimize data workflows using GCP tools such as Dataflow (Apache Beam), Dataproc, BigQuery, Cloud Composer (Airflow), and Pub/Sub
- Develop Java-based data ingestion and transformation applications to move data across structured and unstructured sources
- Collaborate with data architects and analysts to translate business requirements into scalable technical data solutions
- Monitor, troubleshoot, and tune pipeline performance, data quality, and reliability in production environments
- Implement data governance and security best practices including IAM policies, encryption, and access controls
- Work with Cloud Storage, Cloud SQL, Spanner, and Bigtable to manage and persist data assets
- Participate in code reviews, technical design discussions, and agile ceremonies
- Write technical documentation for pipelines, schemas, and data flows
- Support data migration efforts and legacy system integration with modern cloud infrastructure
REQUIRED QUALIFICATIONS
Core GCP Skills
- 5+ years of experience in data engineering with at least 3 years on Google Cloud Platform
- Hands-on expertise with BigQuery (table design, partitioning, clustering, cost optimization)
- Proficiency with Cloud Dataflow (Apache Beam pipelines — batch and streaming)
- Experience with Cloud Composer / Apache Airflow for workflow orchestration
- Familiarity with Pub/Sub for real-time event streaming and messaging
- Working knowledge of Cloud Storage, Dataproc (Spark/Hadoop), and GCP networking basics
Java & ETL
- Strong proficiency in Java (8+) for building data pipelines and backend services
- Experience designing and building ETL/ELT pipelines at scale (batch and streaming)
- Knowledge of SQL and experience writing complex queries for BigQuery or similar warehouses
- Familiarity with data transformation patterns: slowly changing dimensions, CDC, data normalization
- Experience integrating APIs, JDBC/ODBC connectors, and file-based data sources
General
- Solid understanding of distributed systems, data warehousing concepts, and data lake architecture
- Proficiency with version control (Git) and CI/CD practices
- Excellent problem-solving skills and ability to work independently in a contract environment
- Strong communication skills for collaborating with remote and on-site stakeholders
PREFERRED / NICE-TO-HAVE
- Google Cloud Professional Data Engineer certification
- Experience with dbt (data build tool) for data transformation
- Familiarity with Terraform or Deployment Manager for infrastructure-as-code on GCP
- Experience with Kafka or other streaming platforms alongside Pub/Sub
- Knowledge of Python for scripting and data manipulation tasks
- Exposure to data quality frameworks (Great Expectations, Deequ)
- Experience with Looker, Data Studio, or other BI tools connected to BigQuery
TECHNICAL SKILLS SUMMARY
Google Cloud Platform (GCP)
BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, Cloud SQL, Spanner, Bigtable
Java (primary), SQL, Python (preferred)
Apache Beam, Apache Spark, Apache Airflow, dbt
Git, CI/CD pipelines, Terraform (preferred)
Avro, Parquet, JSON, CSV, ORC
Agile / Scrum, Data Mesh, Data Lakehouse
ABOUT THE ENGAGEMENT
This is a contract role embedded within an established data engineering team. You will have direct impact on mission-critical data pipelines that serve business intelligence, analytics, and operational systems. The team follows agile practices with two-week sprints, daily standups, and collaborative design sessions. The role is hybrid with approximately three days on-site in Denver, CO.