Databricks Architect

SparkHive; United States; Remote; USD 70,000 - 120,000; Full time

Job summary

A growing Databricks Consulting Partner seeks a Databricks Architect for a 6-month contract role. Ideal candidates will have at least 10 years in data engineering, with strong expertise in Databricks, Spark, and cloud platforms. Enjoy a fast-paced and innovative environment, leading projects to deliver robust data solutions.

Benefits

Competitive hourly rate based on experience

Opportunity to work with a high-growth startup

Qualifications

• 10+ years of experience in data engineering or architecture roles.
• 5+ years of hands-on experience with Databricks.
• Strong expertise in Spark (preferably PySpark), Delta Lake, and SQL.

Responsibilities

• Architect and design end-to-end data solutions using the Databricks Lakehouse Platform.
• Guide clients through data engineering best practices and architecture decisions.
• Mentor junior team members and ensure best practices in coding and design.

Skills

Data Engineering

Data Architecture

Spark

SQL

Cloud Solutions

Communication

Job description

Direct message the job poster from SparkHive

Job Title: Databricks Architect (Contract)

Location: Remote (must be in the US)

Contract Type: 6-month contract (with potential to extend)

Start Date: ASAP

Company: Databricks Consulting Partner

About:

A fast-growing Databricks Consulting Partner focused on helping organizations unlock the power of data with scalable, cloud-native architectures. We work with startups, scaleups, and enterprise clients across industries, delivering end-to-end solutions on the Databricks Lakehouse Platform. As a startup, we move fast, innovate constantly, and value pragmatic problem-solving.

Role Overview:

We’re looking for a Databricks Architect with strong hands-on experience designing and implementing scalable data solutions using the Databricks platform. This is a contract role ideal for someone who thrives in fast-paced environments and is comfortable leading technical engagements from architecture through delivery.

Responsibilities:

• Architect and design end-to-end data solutions using the Databricks Lakehouse Platform.
• Guide clients through data engineering best practices, architecture decisions, and cloud-native designs (Azure/AWS).
• Build scalable pipelines using Spark (PySpark/Scala), Delta Lake, and MLflow.
• Collaborate with client stakeholders, data engineers, and analysts to align business goals with technical solutions.
• Lead technical workshops and discovery sessions with clients.
• Create architecture diagrams, technical documentation, and delivery roadmaps.
• Mentor junior team members and ensure best practices in coding and design.
• Act as a technical advisor to help clients scale their Databricks usage effectively.

Required Qualifications:

• 10+ years of experience in data engineering or architecture roles.
• 5+ years of hands-on experience with Databricks.
• Strong expertise in Spark (preferably PySpark), Delta Lake, and SQL.
• Proven experience designing and building data platforms on Azure and/or AWS.
• Deep understanding of data warehousing, ETL pipelines, and data lake architectures.
• Strong communication skills and client-facing experience.
• Comfortable working in agile, startup-like environments.

Preferred Qualifications:

• Databricks Certified Data Engineer or Solutions Architect.
• Experience with MLflow, Unity Catalog, or dbt.
• Familiarity with CI/CD for data pipelines.
• Prior consulting experience strongly preferred.

What We Offer:

• Competitive hourly rate (commensurate with experience).
• Opportunity to work with a high-growth, Databricks-focused startup.
• Exposure to diverse industries and challenging technical problems.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology and Consulting

• Industries

  IT Services and IT Consulting

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