Databricks Data Architect

Job Title: Databricks Data Architect Location: Dallas, TX Job Summary We are seeking an experienced Databricks Data Architect to design and drive scalable, secure, and high-performance enterprise data solutions. The ideal candidate will have deep expertise in Databricks, Apache Spark, Delta Lake, cloud data platforms, and modern data architecture, with strong experience designing data ingestion, transformation, governance, and analytics solutions.

Key Responsibilities

• Define and implement enterprise-scale Databricks data architecture and technical standards.
• Design scalable Lakehouse architectures using Databricks, Delta Lake, and cloud-native services.
• Architect batch and streaming data pipelines for structured and unstructured data.
• Establish Bronze, Silver, and Gold data-layer design patterns.
• Provide technical leadership for data engineering teams developing solutions using PySpark, Spark SQL, Python, and/or Scala.
• Design reusable frameworks for data ingestion, transformation, data quality, monitoring, and error handling.
• Drive implementation of Unity Catalog for centralized data governance, access control, lineage, and metadata management.
• Define standards for performance optimization, cluster/compute utilization, partitioning, and workload management.
• Design secure integrations between Databricks and enterprise data sources, APIs, cloud storage, BI platforms, and downstream applications.
• Support migration and modernization of legacy ETL/data warehouse workloads to the Databricks Lakehouse platform.
• Partner with Data Engineering, BI/Analytics, Security, Governance, Infrastructure, and business teams to translate requirements into scalable technical solutions.
• Conduct architecture/design reviews and provide technical guidance to engineering teams.
• Establish best practices around CI/CD, Git, automated testing, deployment, observability, and DevOps for data workloads.

Required Skills

• Strong hands-on experience with Databricks and Apache Spark.
• Strong knowledge of Delta Lake and Lakehouse architecture.
• Advanced proficiency in PySpark, Spark SQL, SQL, and Python; Scala experience is a plus.
• Experience with Unity Catalog, data governance, RBAC, lineage, and security.
• Experience designing large-scale ETL/ELT and data integration solutions.
• Strong understanding of dimensional modeling, normalized models, data marts, and enterprise data architecture.
• Experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience with orchestration technologies such as Databricks Workflows, Apache Airflow, Azure Data Factory, or equivalent.
• Understanding of REST APIs, event/stream processing, and formats such as JSON, Parquet, and Avro.
• Knowledge of CI/CD and infrastructure automation using tools such as Git, Azure DevOps/GitHub, Terraform, or equivalent.
• Strong troubleshooting and performance-tuning skills.

Preferred Qualifications

• 10+ years of overall Data Engineering/Data Architecture experience.
• 3+ years of architecture/design experience with Databricks or comparable modern cloud data platforms.
• Experience delivering enterprise-scale cloud data modernization programs.
• Experience integrating Databricks with Power BI or other enterprise reporting platforms.
• Databricks certification, such as Databricks Certified Data Engineer Professional, is preferred.
• Strong communication skills with the ability to work with both engineering teams and senior stakeholders.

Key Competencies Databricks | Apache Spark | PySpark | SQL | Python | Scala | Delta Lake | Unity Catalog | Lakehouse | Data Modeling | ETL/ELT | Data Governance | Cloud Architecture | CI/CD | Terraform | Power BI

What I changed: I structured this as a senior, hands-on architect JD rather than a generic Data Engineer description, with particular emphasis on Databricks architecture, Unity Catalog, governance, scalability, and technical leadership