Tangentia

Databricks Technical Architect

Tangentia$125K — $150K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years in Data Engineering/Data Architecture
  • Hands-on expertise in Databricks, Apache Spark, PySpark, and SQL
  • Experience with cloud platforms such as Azure Databricks, AWS, or GCP
  • Knowledgeable in Delta Lake and Data Lakehouse architecture
  • Familiarity with CI/CD, DevOps, and integration tools
  • Proficient in stakeholder management and solution architecture

Responsibilities

  • Design and implement enterprise-scale data platforms using Databricks
  • Define data architecture, governance, security, and best practices
  • Build and optimize ETL/ELT pipelines using Spark, PySpark, and SQL
  • Collaborate with business and technical stakeholders
  • Lead migration of legacy data platforms to Databricks and cloud
  • Provide technical leadership and architecture guidance
  • Optimize performance, scalability, and cost efficiency of data workloads

Benefits

  • Comprehensive health insurance
  • 401(k) retirement plan
  • Generous PTO and paid holidays
  • Professional development opportunities
  • Flexible work hours and remote work options
Full Job Description
Job Summary: We are seeking an experienced Databricks Technical Architect to design, architect, and implement scalable data and analytics solutions on the Databricks platform. The ideal candidate will have strong expertise in data engineering, cloud technologies, big data frameworks, and modern data architectures.

Key Responsibilities:
  • Design and implement enterprise-scale data platforms using Databricks.
  • Define data architecture, governance, security, and best practices.
  • Build and optimize ETL/ELT pipelines using Spark, PySpark, and SQL.
  • Collaborate with business and technical stakeholders to deliver data solutions.
  • Lead migration of legacy data platforms to Databricks and cloud environments.
  • Provide technical leadership, solution design, and architecture guidance.
  • Optimize performance, scalability, and cost efficiency of data workloads.

Required Skills:
  • 8+ years of experience in Data Engineering/Data Architecture.
  • Strong hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
  • Experience with Azure Databricks, AWS, or GCP cloud platforms.
  • Knowledge of Delta Lake, Data Lakehouse architecture, and data governance.
  • Experience with CI/CD, DevOps, and data integration tools.
  • Strong stakeholder management and solution architecture skills.

Preferred Certifications:
  • Databricks Certified Data Engineer/Architect
  • Azure Solutions Architect or relevant Cloud Certifications

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