Overview
Remote
On Site
Hybrid
$60 - $80
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 36 Month(s)
Able to Provide Sponsorship
Skills
Analytical Skill
Apache HTTP Server
Apache Kafka
Apache Spark
Artificial Intelligence
Cloud Computing
Collaboration
Communication
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Architecture
Data Flow
Data Integrity
Data Modeling
Data Quality
Data Warehouse
Databricks
ELT
Energy
Extract
Transform
Load
Good Clinical Practice
Google Cloud
Google Cloud Platform
Kubernetes
Machine Learning (ML)
Management
Performance Tuning
Problem Solving
Python
Real-time
SQL
Soft Skills
Terraform
Vertex
Workflow
Job Details
We are looking for a highly capable Data Engineer to design, build, and maintain reliable, scalable data pipelines and infrastructure on Google Cloud Platform (Google Cloud Platform).. The ideal candidate is proficient with BigQuery, Dataflow, and has experience integrating modern tools like Vertex AI and Gemini models for intelligent data workflows.
Core Responsibilities:
- Data Pipeline Development: Build scalable batch and real-time pipelines using Dataflow, Pub/Sub, Cloud Composer, and Dataproc.
- Data Warehousing: Design and optimize analytical models in BigQuery, implementing best practices in schema design and performance tuning.
- Infrastructure & CI/CD: Deploy data infrastructure with Terraform; create and manage CI/CD pipelines for workflow automation.
- Data Quality & Governance: Implement validation checks, ensure data integrity, and enforce security and governance practices.
- AI/ML Integration: Collaborate with data scientists to support Vertex AI workflows and explore the use of Gemini models (via BigQuery ML or Vertex AI APIs) for advanced data transformation.
- Cross-Team Collaboration: Work with analysts, scientists, and business stakeholders to deliver impactful data solution.
Technical Skills:
- Strong experience with Google Cloud Platform services: BigQuery, Dataflow, Pub/Sub, Cloud Storage
- Expertise in SQL, Python, and ETL/ELT development
- Knowledge of Infrastructure as Code tools (e.g., Terraform)
- Familiarity with CI/CD tools: Google Cloud Build, Jenkins
- Understanding of data modeling, partitioning, clustering, and materialized views
- Working knowledge of data quality frameworks and governance principles
- Experience with Vertex AI, or a strong interest in ML/AI workflows on Google Cloud Platform
- Apache Spark, Kafka, Apache Airflow
- DBT or Dataform for transformations
- Docker, Kubernetes for Containerization
- Snowflake, Databricks or other modern platforms
Soft Skills:
- Strong communication and collaboration skills
- Ability to manage priorities and work independently
- Analytical thinking and problem-solving mindset
Preferred Skills (Bonus):
- Google Cloud certifications (e.g., Professional Data Engineer, ML Engineer)
- Domain experience in energy, utilities, or industrial sectors
Experience Requirements:
- Education: Bachelor s degree in computer science, Engineering, Statistics, or related technical field (or equivalent experience)
- Professional Experience:
- 6-8 years of experience in data engineering
- Proven hands-on experience with Google Cloud Platform and modern data architecture
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.