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GCP DATA ENGINEER Contract • Denver, Colorado • On-site / Hybrid |
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Position Type |
Contract (1099 / C2C) |
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Duration |
6–12 Months (with extension potential) |
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Location |
Denver, Colorado —5 days on-site |
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Start Date |
Immediate / ASAP |
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Industry |
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
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Category |
Technologies & Tools |
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Cloud Platform |
Google Cloud Platform (GCP) |
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GCP Services |
BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, Cloud SQL, Spanner, Bigtable |
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Programming |
Java (primary), SQL, Python (preferred) |
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ETL / Pipeline |
Apache Beam, Apache Spark, Apache Airflow, dbt |
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DevOps / IaC |
Git, CI/CD pipelines, Terraform (preferred) |
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Data Formats |
Avro, Parquet, JSON, CSV, ORC |
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Methodologies |
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.