Senior Data Engineer – Databricks & AWS

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

Job summary

Quantum Technologies. LLC in Sunnyvale, CA is seeking a Senior Data Engineer specialized in Databricks and AWS to build scalable data pipelines and data platforms. You will work with Python, PySpark, SQL, and modern cloud data architectures to enable enterprise analytics and AI-powered insights.

The role demands 8+ years in data engineering, strong Databricks, Delta Lake, and AWS experience, plus a track record of delivering robust data solutions in fast-paced environments.

Qualifications

• 8+ years in data engineering.
• Strong Python, PySpark, SQL experience.
• Hands-on Databricks and Delta Lake expertise.
• Cloud experience with AWS services (S3, Glue, Lambda, Redshift, EMR).
• Snowflake or other cloud data warehouses experience.
• Strong data modeling and warehousing knowledge.
• Spark and distributed data processing experience.
• Knowledge of data integration and orchestration tools.
• Experience with Git, Jenkins, and CI/CD pipelines.
• Strong data quality, performance tuning, and governance knowledge.
• Modern skills 2025–2026: Unity Catalog, Lakehouse, Workflows, Genie., MCP integration.

Responsibilities

• Design, develop, and maintain scalable data 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

AWS

Snowflake

Data Modeling

Data Warehousing

Spark

CI/CD

Terraform

Data Quality

Data Governance

Git

Jenkins

Perf Tuning

Tools

Databricks

Delta Lake

Terraform

Git

Jenkins

CI/CD

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.