Senior Databricks Engineer/Architect

Virtasant · posted yesterdayFresh: apply early

Open to candidates in United States

Senior

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What this job asks for

Extracted by RemoteHunt

Must have

•Databricks expertise
•PySpark development
•Data pipeline design
•Data migration to Databricks
•ETL/ELT workflow development

Nice to have

•Cloud platform modernization
•FinOps best practices

Tools and technologies

Databricks, PySpark, ETL, ELT

Worth checking before you apply

1099 contract

Read the full posting

Senior Databricks Engineer/Architect

Job Type: 1099 contract, long-term & ongoing

Location: Remote in US

About Virtasant

Virtasant is a global technology services company with a network of over 4,000 technology professionals across 130+ countries.

We help organizations modernize cloud platforms, improve engineering efficiency, and optimize cloud spend through architecture, automation, and FinOps best practices.

Our teams work directly with enterprise customers to identify inefficiencies, drive modernization efforts, and deliver measurable business outcomes.

What We're Looking For

Experienced Senior Data Engineer or Data Architect specializing in designing, developing, and optimizing scalable data pipelines using PySpark and Databricks.

Skilled in architecting and executing data migrations to Databricks, modernizing data platforms, and building robust ETL/ELT workflows that ensure data quality, performance, and reliability.

Adept at translating complex technical requirements into effective data solutions, collaborating with cross-functional teams, and presenting technical strategies, architecture designs, and project outcomes to business stakeholders and leadership.

What You'll Do

Design, develop, and maintain scalable, high-performance data pipelines.
Architect and lead data migration strategies to the Databricks platform.
Develop and optimize complex data transformations using PySpark.
Build and enhance ETL/ELT processes to support enterprise data initiatives.
Ensure data quality, integrity, scalability, and performance across data platforms.
Present technical solutions, migration roadmaps, and project progress to stakeholders.
Bridge the gap between technical teams and business stakeholders to align data solutions with organizational objectives.