Senior Data Engineer – Databricks & AWS

Ethereum Technologies; Sunnyvale (CA); On-site; USD 76,000 - 108,000; Full time

Job summary

Ethereum Technologies in Sunnyvale, CA is seeking a Senior Data Engineer focused on Databricks and AWS to design scalable data pipelines and enterprise data platforms.

You will work with Python, PySpark, SQL, and modern data lakehouse architectures, optimize Spark jobs, and contribute to AI-powered data solutions. This contract role features a $67/hour bill rate and a strong emphasis on hands-on delivery.

Qualifications

• 8+ years of experience in Data Engineering.
• Strong Python, PySpark, and SQL skills.
• Hands-on Databricks and Delta Lake experience.
• Strong knowledge of ETL/ELT pipeline development.
• Experience with AWS services (S3, Glue, Lambda, Redshift, EMR).
• Snowflake or other cloud data warehouses experience.
• Data modeling and data warehousing knowledge.
• Experience with Spark and distributed data processing.
• Knowledge of data integration and orchestration tools.
• Experience with Git, Jenkins, and CI/CD pipelines.
• Strong understanding of data quality, performance tuning, and optimization.
• Recent / Modern Skills (2025–2026).
• Databricks Unity Catalog and data governance.
• Databricks Lakehouse architecture.
• Databricks Workflows and Delta Live Tables.
• Databricks Genie and Genie Agents.
• Model Context Protocol (MCP) integration.
• Conversational analytics and Text-to-SQL.
• AI-powered data engineering and automation.
• Vector search and RAG integration with enterprise data.
• Data pipeline observability and monitoring.
• Infrastructure as Code using Terraform.

Responsibilities

• Design, develop, and maintain scalable data engineering pipelines.
• Build ETL/ELT workflows using Python, PySpark, and SQL.
• Develop data processing solutions using Databricks and AWS.
• Implement data lakehouse and data warehouse architectures.
• Optimize Spark jobs and large-scale data processing workloads.
• Implement data quality checks and data governance practices.
• Integrate enterprise data sources into centralized data platforms.
• Collaborate with architects, analysts, and business stakeholders.
• Support production deployments, troubleshooting, and performance tuning.

Skills

Python

PySpark

SQL

Databricks

Delta Lake

ETL/ELT pipelines

AWS

Data modeling

Data warehousing

Spark

CI/CD

Data quality

Performance tuning

AI-powered data engineering

Tools

Databricks

Delta Lake

Snowflake

AWS

Terraform

Git

Jenkins

Genie

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:Senior Data Engineer – Databricks & AWS

Location:Sunnyvale, CA

Duration: 11 Months + Extension

Bill Rate: $67/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description

We are looking for an experienced Senior Data Engineer with strong expertise in Databricks, Python, PySpark, SQL, and cloud-based data engineering. The ideal candidate should have hands-on experience designing scalable data pipelines, implementing ETL/ELT processes, and building enterprise data platforms. Experience with AWS, Snowflake, data lakehouse architecture, and modern AI-powered data solutions is highly desirable.

Required Skills

• 8+ years of experience in Data Engineering.
• Strong experience with Python, PySpark, and SQL.
• Hands-on experience with Databricks and Delta Lake.
• Strong knowledge of ETL/ELT pipeline development.
• Experience with AWS services such as S3, Glue, Lambda, Redshift, and EMR.
• Experience with Snowflake or other cloud data warehouses.
• Strong knowledge of data modeling and data warehousing.
• Experience with Apache Spark and distributed data processing.
• Knowledge of data integration and orchestration tools.
• Experience with Git, Jenkins, and CI/CD pipelines.
• Strong understanding of data quality, performance tuning, and optimization.
• Recent / Modern Skills (2025–2026)
• Databricks Unity Catalog and data governance.
• Databricks Lakehouse architecture.
• Databricks Workflows and Delta Live Tables.
• Databricks Genie and Genie Agents.
• Model Context Protocol (MCP) integration.
• Conversational analytics and Text-to-SQL.
• AI-powered data engineering and automation.
• Vector search and RAG integration with enterprise data.
• Data pipeline observability and monitoring.
• Infrastructure as Code using Terraform.

Responsibilities

• Design, develop, and maintain scalable data engineering pipelines.
• Build ETL/ELT workflows using Python, PySpark, and SQL.
• Develop data processing solutions using Databricks and AWS.
• Implement data lakehouse and data warehouse architectures.
• Optimize Spark jobs and large-scale data processing workloads.
• Implement data quality checks and data governance practices.
• Integrate enterprise data sources into centralized data platforms.
• Collaborate with architects, analysts, and business stakeholders.
• Support production deployments, troubleshooting, and performance tuning.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.