Azure Databricks Engineer; Dallas, TX

Key Responsibilities

• Design, build, and optimize scalable, high‑performance data pipelines and data lakes using Azure Databricks.
• Architect and implement end‑to‑end analytics solutions leveraging Databricks and other Azure services (e.g., Azure Data Lake, Azure SQL, Azure Blob Storage).
• Lead the design of cloud‑based architectures using Azure Databricks for data processing, transformation, and reporting.
• Design and implement ETL/ELT processes to ingest, process, and transform data across various sources (structured and unstructured).
• Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and develop data solutions.
• Manage data integration workflows between Databricks and other platforms like Power BI, Azure SQL, Synapse, etc.
• Optimization & Performance Tuning
  :
  • Identify performance bottlenecks in Databricks environments and optimize clusters, queries, and code.
  • Continuously improve and scale data pipelines to accommodate growing data volumes and business needs.
• Collaboration & Leadership
  :
  • Mentor and guide junior engineers and team members in best practices related to Azure Databricks and data engineering.
  • Work closely with cross‑functional teams (data science, analytics, business intelligence) to deliver integrated solutions.
  • Provide technical leadership in cloud data architecture and data engineering.
• Monitoring & Security
  :
  • Implement monitoring and alerting systems to ensure data pipelines and workflows are running smoothly.
  • Ensure compliance with data security and governance standards across the data ecosystem.
• Continuous Improvement & Innovation
  :
  • Stay up to date with the latest advancements in Azure Databricks, cloud technologies, and data engineering trends.
  • Continuously evaluate and introduce new technologies and methodologies to enhance the data platform.

• Experience
  :
  • Minimum 10 years of hands‑on experience in data engineering and cloud‑based data platforms.
  • At least 5 years of experience working with Azure Databricks, building data pipelines, and performing data engineering tasks.
  • Strong experience with Azure services such as Azure Data Lake, Azure Synapse Analytics, Azure Blob Storage, Azure SQL Database, etc.
• Technical Skills
  :
  • Proficiency in Spark, PySpark, Scala, or SQL for large‑scale data processing.
  • Expertise in Databricks notebooks, clusters, job scheduling, and libraries.
  • Deep understanding of cloud‑native data engineering practices and architecture on Azure.
  • Familiarity with data modeling, data lakes, and data warehouse concepts.
  • Expertise in Azure services:
    Data Factory, Data Lake, Synapse Analytics, Event Hubs, Cosmos DB.
• Data Pipeline and ETL/ELT Development
  :
  • Experience building and optimizing ETL/ELT workflows on Databricks.
  • Knowledge of data orchestration tools such as Azure Data Factory, Apache Airflow, or similar.
• Big Data Technologies
  :
  • Proficiency in handling large‑scale distributed data processing with tools like Apache Spark.
  • Experience with technologies such as Kafka, Delta Lake, and Databricks Runtime.
  • Strong understanding of Delta Lake and Lakehouse architecture.
• Programming Languages
  :
  • Strong programming skills in Python, Scala, or Java.
  • Experience with SQL‑based querying and optimizations.
• Cloud & Dev Ops
  :
  • Strong understanding of Azure cloud services and architecture.
  • Familiarity with Dev Ops principles, CI/CD pipelines, and automation tools. Terraform required.
  • Knowledge of Git, Azure Dev Ops, or similar version control and deployment systems.
• Collaboration & Leadership
  :
  • Excellent communication skills to work with both technical and non‑technical stakeholders.
  • Proven track record of mentoring and leading teams of data engineers.
  • Experience managing complex projects and working with cross‑functional teams.

• Certifications
  :
  • Microsoft Certified:
    Azure Data Engineer Associate or equivalent certification.
  • Databricks Certified Associate Developer for Apache Spark.
• Education
  :
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.