Google Cloud Platform Data Engineer

HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for GCP Data Engineer / Architect in Remote . Below is the detailed job description.

Role Title: GCP Data Engineer / Architect

Role Type: Contract

Work Location: Remote

Position Overview

The ideal candidate will design, build, and maintain scalable, production-grade batch and streaming data pipelines using core Google Cloud Platform (Google Cloud Platform) technologies.

Key Responsibilities

• Pipeline Development: Design, build, and optimize scalable batch and real-time data ingestion pipelines using Google Cloud Platform Dataflow, Pub/Sub, and Cloud Composer (Airflow).

• Data Warehousing & Modeling: Create optimized data architectures and dimensional models in BigQuery to support enterprise analytics, reporting, and data science teams.

• Data Integration & Transformation: Develop clean, scalable Python code and complex SQL scripts/dbt models for ETL/ELT workflows.

• Cloud Storage & Security: Manage data storage strategies on Cloud Storage (GCS) and implement IAM security, data masking, and access controls.

• Performance Tuning & Optimization: Monitor pipeline execution, conduct data profiling, and optimize BigQuery query performance and resource utilization to minimize operational costs.

• Collaboration: Partner with cross-functional teams (Data Analysts, Data Scientists, and Business Stakeholders) to gather requirements and translate them into robust technical solutions.

• Experience: 5+ years of hands-on data engineering experience, with at least 3+ years dedicated to Google Cloud Platform data services.

• Google Cloud Platform Stack: Deep expertise in BigQuery, Cloud Storage (GCS), Dataflow, Pub/Sub, and Cloud Composer (Apache Airflow).

• Programming & SQL: Strong proficiency in Python (for data processing/scripting) and Advanced SQL (window functions, optimization, complex joins).

• ETL/ELT & Orchestration: Proven experience building idempotent workflows and data pipelines (e.g., using dbt, Airflow, or Dataflow).

• Data Warehousing: Solid understanding of data modeling principles (Star Schema, Snowflake Schema, SCD Type I/II).