What are the responsibilities and job description for the Azure Databricks Lead/Architect position at Lorven Technologies, Inc.?
Job Details
Job Title: Azure Databricks Lead/Architect
Location: Chicago, IL (Hybrid)
Duration: 12 months
Experience: 12 years
Required Skills & Experience:
- 12 years of professional experience in Data Engineering, Architecture, or Data Platforms.
- 5 years of hands-on experience with Azure Databricks, Apache Spark, and PySpark.
- Deep expertise in ETL design, data modelling (Data Vault, Star Schema, Medallion architecture), and query optimization.
- Strong experience with SQL, Python, and Data Pipeline Orchestration.
- Hands-on experience in CI/CD practices, GitHub Actions, and version control tools.
- Expertise in Azure ecosystem (Azure Data Lake Storage, Azure Data Factory, Synapse Analytics, Event Hub, Kafka).
- Knowledge of structured streaming and real-time data processing.
- Experience implementing security and governance best practices for cloud-based data platforms.
Responsibilities:
- Architecture & Strategy:
- Design and develop scalable Lakehouse architectures that enable high-performance data ingestion, processing, and analytics.
- Define and enforce best practices for ETL, data modeling, and data governance within the Azure ecosystem.
- Architect and optimize Medallion Architecture (Bronze, Silver, Gold) for efficient data transformation and analytics.
- Ensure high availability, security, and performance of Azure Databricks environments.
- Define data infrastructure strategies, ensuring alignment with business objectives and scalability requirements.
- Technical Leadership & Development:
- Provide architectural guidance and hands-on development support for ETL pipelines, batch & streaming solutions in Azure Databricks using PySpark and SQL.
- Drive the implementation of Data Vault, Star Schema, and Data Warehouse modeling techniques.
- Implement CI/CD pipelines, version control, and automation to streamline deployment and testing.
- Lead the integration of Azure Data Services such as Azure Data Factory, Azure Synapse, Delta Lake, and Delta Live Tables.
- Apply Chaos Engineering practices to ensure system resilience and fault tolerance.
- Collaboration & Mentorship:
- Work closely with Product Owners, Data Engineers, Data Scientists, and Business Analysts to deliver high-quality data solutions.
- Provide technical mentorship to engineering teams, enabling them to follow best practices in Databricks development, ETL, and data pipeline management.
- Collaborate across departments to design functional and scalable solutions that balance business needs and technical feasibility.
- Analytics & Optimization:
- Conduct performance tuning and optimization of Databricks workloads, Spark jobs, and SQL queries.
- Define and implement monitoring frameworks to track data quality, lineage, and processing performance.
- Design efficient data governance, access control, and security policies for Databricks and Azure environments.
- Lead root-cause analysis and problem-solving for complex data engineering challenges.
Preferred Skills (Bonus Points):
- Experience with Snowflake and BI Tools (Power BI, Tableau).
- Exposure to Graph Databases and Knowledge Graphs.
- Familiarity with Machine Learning or AI-based data solutions in Databricks.
- Experience in Python library development for reusable data processing functions.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
