Why This Role Stands Out
This on-site Data Architect role offers a fantastic opportunity to shape enterprise data solutions within a reputable company, leveraging your expertise in Databricks and AWS to drive innovation. You'll thrive here if you possess strong skills in cloud data architecture, ETL/ELT, and data modeling, and are eager to mentor others and contribute to cutting-edge initiatives. Apply today to make a significant impact with a competitive hourly rate of $100.
Quick Overview
Job Description
Data Architect – Databricks/AWS
Location: New York, NY – Onsite
Rate: $100 per hour W2
Duration: 12+ months
W2 only – No C2C or third-party agencies
Must Have Skills
Databricks and Unity Catalog
AWS cloud data architecture
PySpark, Python, Spark and SQL
ETL/ELT pipelines
Data modeling and governance
GitLab CI/CD and Infrastructure as Code
Tableau and BI architecture
Position Summary
We are seeking an experienced Data Architect to design scalable enterprise data solutions using Databricks and AWS. This role will lead cloud data architecture, data pipelines, governance, modeling and analytics within a complex, highly regulated environment.
Responsibilities
Architect Databricks and AWS data platforms for large-scale analytical workloads.
Design ETL/ELT pipelines, lakehouse solutions and dimensional data models.
Integrate Unity Catalog, AWS IAM and cross-account data access.
Develop standards for PySpark, Python, Spark and SQL.
Establish data quality, governance, security and access-control frameworks.
Optimize compute, storage, clusters and overall platform costs.
Implement GitLab CI/CD and Infrastructure as Code practices.
Design semantic layers for Tableau and BI reporting.
Support MLOps and generative AI initiatives.
Partner with technical and business teams and mentor data engineers.
Qualifications
Bachelor’s degree in computer science or a related field.
8+ years of data architecture, data engineering or database design experience.
Extensive Databricks and AWS cloud data architecture experience.
Strong PySpark, Python, Spark, SQL and ETL/ELT expertise.
Expert knowledge of data modeling, lakehouses, data warehouses and governance.
Experience delivering secure, scalable and highly available data platforms.
Strong communication and cross-functional leadership skills.
Tableau, MLOps and Domino Data Lab experience preferred.
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