US_East | Data Engineer_L4

 
Role Name: Senior Data Engineer
Work site: US (Remote)
 
We have a request for a Sr Data Engineer . Assignment details below:
· Start Date: July 20, 2026
· End Date: January 8, 2027
· Allocation: 40 hrs per week
· Time Zone: US Remote, CST
· Must be US Citizen
We are seeking a sr Data Engineer with a heavy focus on Cloud Platform
Senior Data Engineer
Location: CST preferred
Immigration Status: Must be US Citizen
Role Overview
We are seeking a highly skilled Senior Data Engineer to lead the architectural design and hands-on implementation of our next-generation data platform on Cloud Platform (GCP). The ideal candidate is a subject matter expert in BigQuery and possesses deep experience building robust, scalable data pipelines using Dataform, Dataflow, and Dataproc.
In this role, you will bridge the gap between high-level architectural strategy and technical execution, ensuring our data ecosystem is performant, cost-effective, and capable of supporting advanced analytics and machine learning initiatives.
Key Responsibilities
Architectural Design & Leadership
Design and implement end-to-end data architectures on GCP, ensuring high availability, security, and scalability.
Establish best practices for data modeling (Medallion architecture, Star Schema) specifically optimized for BigQuery's columnar storage.
Evaluate emerging GCP technologies and provide strategic recommendations for platform evolution.
Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
Data Pipeline Engineering
Develop complex ELT workflows using Dataform to manage SQL-based transformations, ensuring data lineage and quality through automated testing.
Build and maintain large-scale batch and streaming data processing pipelines using Dataflow (Apache Beam).
Preferred to have Dataproc knowledge for distributed processing of massive datasets using Spark or Hadoop where specialized compute is required
Integrate data from various sources (SaaS APIs, RDBMS, NoSQL) into the central BigQuery data warehouse.
Performance & Governance
Optimize BigQuery performance through partitioning, clustering, and materialized views while managing cost through efficient slot utilization.
Implement CI/CD pipelines for data infrastructure and code deployments using Cloud Build or similar tools.
Ensure data governance standards are met by implementing Identity and Access Management (IAM), data masking, and encryption.
Technical Requirements
Category
Required Expertise
Data Warehousing
Advanced BigQuery (Storage optimization, BQML, Analytics Functions)
Transformation
Expert-level Dataform (SQLX, JavaScript, Project Configuration), understand Cortex CDC and Merge logical code logic and flow
Stream & Batch
Hands-on Dataflow (Apache Beam in Java or Python)
Big Data Compute
Dataproc (Spark, Hive, Hadoop ecosystem)
Programming
Proficiency in Python, Java, or Go; Expert SQL skills
Orchestration
Dataform code generation and custom namespace configuration. Cloud Composer (Airflow) or Vertex AI Pipelines
Infrastructure
Terraform for GCP Resource Provisioning (IaC)
Qualifications
Experience: data engineering, with at least 3 years focused heavily on Cloud Platform.
Architecture: Proven track record of designing data platforms from the ground up that support both BI and Data Science workloads.
Hands-on Skills: Ability to write clean, maintainable, and production-ready code.
Soft Skills: Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred Certifications
Professional Data Engineer
Professional Cloud Architect
Knowledge of SAP Data model and SAP HANA required / preferred