GCP Data Engineer

The Smart

Denver, CO, United States

11 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$83,200.0 - $166,400.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Adobe Analytics Artificial Intelligence Data Analysis Cloud Database Continuous Integration Information Engineering Data Integration Extract Transform Load (ETL) Data Mart Data Transformation Data Mining Data Systems

+22 more

Data Warehousing Database Queries Dimensional Modeling Github Python (Programming Language) Power BI Software Engineering SQL Databases Data Streaming Systems Integration Tableau (Software) Data Logging Data Processing Freeform SQL Google Cloud Sql Optimization Delivery Pipeline Large Language Models Restful APIs Looker Analytics Data Pipelines Api Management

Job description

As a GCP Data Engineer, you will design and build cloud-based data products, automated data pipelines, and analytical data marts that support business intelligence, analytics, and AI-driven initiatives. You will leverage Google Cloud Platform, Python, SQL, and API integrations to deliver scalable, reliable, and well-documented data solutions that support enterprise reporting and decision-making., * Design and develop scalable data marts and analytical data products within Google Cloud Platform.

Build automated pipelines that ingest, transform, and validate data from third-party APIs and enterprise systems.
Develop Python-based solutions for API integrations, data extraction, transformation, and automation.
Create and optimize complex SQL queries to support data integration, reporting, and analytics.
Design data models that support business intelligence, reporting, analytics, and AI use cases.
Integrate marketing, business, and external data sources into curated analytical datasets.
Implement data quality controls, monitoring, logging, reconciliation, and exception handling processes.
Maintain and enhance existing digital marketing data marts and reporting datasets.
Create comprehensive technical documentation covering architecture, data flows, business rules, and support procedures.
Collaborate with analytics, engineering, security, architecture, and production support teams to deliver production-ready solutions.

Requirements

Professional experience in Data Engineering, Analytics Engineering, Software Engineering, or a related technical discipline.
Advanced SQL expertise with the ability to write, optimize, and troubleshoot complex queries.
Strong Python development experience for API integration, automation, and data transformation.
Hands-on experience building ETL/ELT pipelines and analytical data models.
Experience integrating and processing data from REST APIs and third-party platforms.
Strong experience working with Google Cloud Platform and cloud-based data services.
Knowledge of dimensional modeling, data warehousing concepts, data grain, and reusable analytical assets.
Experience implementing data quality validation, monitoring, logging, and exception management solutions.
Strong technical documentation, communication, and stakeholder collaboration skills.
Experience with dbt, dlt, DuckDB, Adobe Analytics, BI platforms (Tableau, Looker, Power BI), AI/LLM technologies, GitHub, CI/CD, and highly regulated industries is preferred.