Senior Data Engineer – Databricks & AWS

Valiant Technologies LLC; Sunnyvale (CA); On-site; USD 83,000 - 103,000; Full time

Job summary

Valiant Technologies LLC in Sunnyvale, CA, is seeking a Senior Data Engineer with deep expertise in Databricks, Python, PySpark, SQL, and cloud data platforms.

You will design scalable data pipelines, implement ETL/ELT processes, and build enterprise data solutions using AWS, Snowflake, and lakehouse architectures. Strong data modeling and governance are essential in this role.

Qualifications

• 8+ years of experience in Data Engineering.
• Strong experience with Python, PySpark, and SQL.
• Hands-on experience with Databricks and Delta Lake.
• Experience with AWS services such as S3, Glue, Lambda, Redshift, and EMR.
• Strong knowledge of data modeling and data warehousing.
• Experience with Spark and distributed data processing.
• Knowledge of data integration and orchestration tools.
• Experience with Git, Jenkins, and CI/CD pipelines.

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

ETL/ELT pipelines

Data modeling

Data warehousing

Spark

Data governance

Data quality

AI-powered data engineering

Vector search

RAG integration

Data pipeline observability

Terraform

Tools

Databricks

Delta Lake

AWS

Snowflake

Git

Jenkins

Terraform

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.