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GCP DATA ENGINEER

Contract • Denver, Colorado • On-site / Hybrid

Position Type

Contract (1099 / C2C)

Duration

6–12 Months (with extension potential)

Location

Denver, Colorado —5 days on-site

Start Date

Immediate / ASAP

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

Category

Technologies & Tools

Cloud Platform

Google Cloud Platform (GCP)

GCP Services

BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, Cloud SQL, Spanner, Bigtable

Programming

Java (primary), SQL, Python (preferred)

ETL / Pipeline

Apache Beam, Apache Spark, Apache Airflow, dbt

DevOps / IaC

Git, CI/CD pipelines, Terraform (preferred)

Data Formats

Avro, Parquet, JSON, CSV, ORC

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.