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CHI Software
Open role>14 days

Data Engineer/Architect (Databricks)

CHI Software
Work model
Not specified
Experience
5+ years
Employment
Not specified
Compensation
Not disclosed
Technology signal
17 tags

Technology context

17

Parsed from the vacancy text; ordered by relevance to this role.

AIAWSMachine LearningAzureGCPData ScienceMLOpsCloudReliability EngineeringKafkadbtScalabilitySparkDatabricksScalaSQLAirflow

Full listing

Role description

We are looking for a Data Engineer/Data Architect (Databricks) to help build and evolve our clients' data platforms. You'll design, build, and maintain the pipelines and architecture that power analytics and machine learning across a range of projects.

This is a fully remote position, work from anywhere in the U.S., in the time zone that suits you, with a flexible schedule and minimal bureaucracy.

What You'll Do

  • Design and build ETL/ELT pipelines on Databricks and Apache Spark
  • Build and maintain Delta Lake architectures (bronze/silver/gold layers)
  • Contribute to data governance, access control, and metadata management (e.g., Unity Catalog)
  • Optimize Spark job performance and manage cloud infrastructure costs
  • Design data models and architectural patterns for analytics and ML use cases
  • Set up and maintain pipeline orchestration (Databricks Workflows, Airflow)
  • Ensure data quality, reliability and observability across the platform
  • Evaluate tools, frameworks and architectural decisions as the platform scales
  • Collaborate with Data Scientists, Analysts and Product teams to translate business needs into technical solutions
  • Review code and architecture, share knowledge and help raise the engineering bar across the team

Requirements

Must-have

  • 5+ years of experience in Data Engineering, Data Architecture, or a related field
  • Hands-on production experience with Databricks
  • Strong command of Apache Spark (PySpark or Scala)
  • Advanced SQL and experience working with large-scale datasets
  • Experience with Delta Lake
  • Familiarity with at least one major cloud platform (AWS, Azure or GCP)
  • Solid understanding of data modeling, data warehousing, and Lakehouse architecture principles
  • Ability to make and communicate sound technical decisions, whether at the pipeline or platform level

Nice to have

  • Databricks Certified Data Engineer certification (Associate or Professional)
  • Experience with Unity Catalog or similar data governance tools
  • Experience with streaming data processing (Structured Streaming, Kafka)
  • Familiarity with dbt, Airflow, or other orchestration tools
  • Exposure to MLOps / supporting ML pipelines, especially when collaborating with a Data Science team
  • Experience designing or scaling data platforms in a product company with high-volume data operations
  • Experience mentoring engineers or leading technical decisions across a team