Databricks Engineer

Artifintech; Washington (District of Columbia); On-site; USD 150,000 - 210,000; Full time

Job summary

Artifintech in the United States seeks a lead Databricks Engineer who will serve as the principal technical authority for the Databricks Lakehouse platform.

You will drive adoption, implementation, and optimization across data pipelines, analytics, and AI initiatives, collaborating with data engineering, data science, analytics, and infrastructure teams to design robust, scalable solutions and troubleshoot complex issues.

Qualifications

• Bachelor's degree or equivalent work experience.
• 7+ years in Data Engineering/Architecture with 4+ years in Databricks.
• Experience implementing Unity Catalog with row- and column-level security.
• Deep Spark tuning and performance optimization.
• Experience with MLflow, Vector Search, and Mosaic AI on Databricks.
• Proficiency in Python, Scala, SQL for distributed computing.

Responsibilities

• Lead design and optimization of end-to-end Databricks solutions (Unity Catalog, Delta Lake, Databricks SQL, Workflows, Jobs, Mosaic AI).
• Build scalable data ingestion, transformation, and orchestration pipelines (Spark, Delta Live Tables, Auto Loader).
• Identify and resolve Spark performance bottlenecks; implement auto-scaling and cost optimization.
• Establish Databricks security, governance, and Unity Catalog best practices.
• Support ML teams with MLflow, Vector Search, and AI capabilities.
• Provide root cause analysis and mentor engineers; create internal centers of excellence.

Skills

Databricks

Python

SQL

Spark

Unity Catalog

Delta Lake

MLflow

Vector Search

Mosaic AI

Terraform

GitHub Actions

Azure DevOps

Databricks CLI

Education

Bachelor's degree in IT/CS or related field

Tools

Terraform

Databricks CLI

GitHub Actions

Azure DevOps

Job description

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

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

Job Summary:

This position serves as the principal technical authority for the Databricks Lakehouse platform within the organization. The successful candidate will drive the adoption, implementation, and optimization of Databricks across data pipelines, analytics, and artificial intelligence initiatives. This role requires collaboration with cross-functional teams including data engineering, data science, analytics, and infrastructure to design robust, scalable solutions and troubleshoot complex technical issues.
Key Responsibilities:

• Lead the design, implementation, and optimization of end-to-end solutions on Databricks, including Unity Catalog, Delta Lake, Databricks SQL, Workflows, Jobs, and Mosaic AI.
• Architect, build, and maintain scalable data ingestion, transformation, and orchestration pipelines using Databricks tools such as Spark, Delta Live Tables, and Auto Loader.
• Identify and resolve performance bottlenecks in Spark jobs, clusters, and SQL queries while implementing cost optimization and auto-scaling strategies.
• Establish and enforce Databricks best practices for security, data governance, compliance, and Unity Catalog implementation.
• Support data science and machine learning teams by implementing MLflow, Feature Store, Vector Search, and generative AI capabilities on Databricks.
• Provide root cause analysis and rapid resolution for complex technical issues as the escalation point for production workloads.
• Mentor data engineers, analysts, and developers through training sessions, documentation, and the creation of internal centers of excellence.
• Design seamless integrations between Databricks and cloud platforms, ETL tools, BI tools, data catalogs, and orchestration systems.
• Implement robust monitoring, logging, alerting, and dashboarding for Databricks workloads using native and external tools.
• Evaluate new Databricks features and roadmaps to recommend adoption strategies that drive business value.

Required Qualifications:

• Bachelor's degree in Information Technology, Computer Science, Business Administration, or a related field, or equivalent work experience.
• 7+ years in Data Engineering or Architecture, with at least 4+ years dedicated exclusively to the Databricks ecosystem.
• Proven track record implementing Unity Catalog from scratch, including row- and column-level security and cross-workspace governance.
• Deep, low-level Apache Spark tuning expertise (e.g., managing data skew, optimizing shuffles, utilizing Adaptive Query Execution, caching strategies, and Photon engine optimization).
• Hands-on experience building production-grade Generative AI or LLM applications using Databricks Mosaic AI, Vector Search, and MLflow.
• Advanced proficiency in Python, Scala, and SQL optimized specifically for distributed computing environments
• Production experience with Infrastructure as Code (IaC) tools like Terraform to deploy and manage Databricks workspaces, clusters, and permissions.
• Experience setting up secure network topologies for Databricks, including Private Link/VPC Peering , encryption keys (BYOK), and IP access lists.
• Strong background in CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab) using Databricks Asset Bundles (DABs) or Databricks CLI.

Preferred Qualifications:

• Databricks Certified Solutions Architect or Databricks Certified Data Engineer Professional.
• Databricks Certified Machine Learning Professional.
• Cloud Architecture certification, such as AWS Certified Solutions Architect or Azure Solutions Architect Expert.

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.