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Job Description

Slalom is hiring a Data Engineer to help deliver complex Data and AI projects for teams across Dallas and Houston.

Responsibilities

  • Develop and implement data solutions using Databricks
  • Work with cross-functional teams to design and optimize data pipelines

Requirements

  • 3+ years of data engineering experience
  • 1+ years of hands-on experience designing and developing data pipelines with Databricks
  • Proficiency designing and building robust, scalable configuration-driven data pipelines
  • Proficiency with Big Data platforms including:
    • Apache Spark
    • Presto
    • Amazon EMR
  • Experience with cloud data warehouses including at least one of:
    • Amazon Redshift
    • Snowflake
    • Google BigQuery
  • Strong programming skills using SQL, Python, Java, etc.
  • Exposure to Infrastructure as Code (IaC) tools such as Terraform
  • Familiarity with building DevOps and CI/CD pipelines
  • Exposure to AI/ML tools and workflows including:
    • MLflow
    • Prompt engineering
    • Modern data/AI agentic workflows

Technologies

  • Databricks
  • Apache Spark
  • Presto
  • Amazon EMR
  • Amazon Redshift
  • Snowflake
  • Google BigQuery
  • SQL
  • Python
  • Java
  • Terraform
  • DevOps
  • CI/CD
  • MLflow

Preferred Qualifications

  • Databricks Certification

Compensation and Benefits

  • Hourly pay range: $50/hr to $80/hr
  • Actual compensation depends on skills, experience, qualifications, location, and other relevant factors
  • Meaningful time off and paid holidays
  • Parental leave
  • 401(k) with a match
  • Highly subsidized health, dental, and vision coverage
  • Adoption and fertility assistance
  • Short/long-term disability
  • Yearly $350 reimbursement account for well-being-related expenses
  • Discounted home, auto, and pet insurance

Location

  • Dallas, TX (onsite)
  • Houston, TX (onsite)

Additional Details

  • Business function: Data & analytics
  • Date posted: Tuesday, September 22, 2026
  • Reference ID: 2384
  • Equal Opportunity Employer; reasonable accommodations available during the selection process

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