Dot Net Databricks - Architect

Dot Net Databricks - Architect

Job Description

As Databricks Architect, you will lead the design and implementation of scalable, secure, and high-performance data solutions using the Databricks Lakehouse Platform. You will define architectural standards, guide engineering teams, and collaborate with stakeholders to align data strategies with business goals. Your role will focus on leveraging Databricks unified analytics capabilities to build enterprise-grade data platforms that support advanced analytics, machine learning, and real-time data processing.

Key Responsibilities:

• Define and own the end-to-end architecture of data platforms built on Databricks, including ingestion, transformation, storage, and consumption layers.
• Design and implement Lakehouse architectures using Delta Lake, Unity Catalog, and structured streaming.
• Proven expertise in implementing data governance using Unity Catalog, including fine-grained access control, column-level lineage, data classification, audit logging, and centralized metadata management across workspaces and cloud environments
• Architect scalable ETL/ELT pipelines using Apache Spark, PySpark, and Databricks Workflows.
• Lead the integration of Databricks with enterprise systems such as data catalogs, data quality frameworks, ML platforms, and BI tools.
• Guide teams in implementing CI/CD pipelines, version control, and automated testing for Databricks notebooks and jobs.
• Collaborate with data scientists, engineers, and business stakeholders to support ML model lifecycle management using MLflow.
• Demonstrated experience or familiarity with AI systems such as Databricks DBRX, Mosaic AI, and AutoML, including their integration into data.
• Provide technical leadership in performance tuning, cost optimization, and cluster configuration.
• Conduct architectural reviews, code audits, and mentoring sessions to ensure adherence to standards and scalability.
• Stay current with Databricks innovations and advocate for adoption of new features and capabilities.

Skills / Qualifications:

• Bachelor s or Masters degree in Computer Science, Software Engineering, Information Technology, or related field required.
• 10+ years of experience in data architecture and engineering, with 5+ years in Databricks and Apache Spark.
• Deep expertise with 5+ years in Dot Net
• Deep expertise in Delta Lake, structured streaming, PySpark, and SQL.
• Strong understanding of Lakehouse architecture, data mesh, and modern data stack principles.
• Experience with Unity Catalog, Databricks Repos, Jobs API, and Workflows.
• Proven ability to design and implement secure, governed, and highly available data platforms.
• Familiarity with Azure cloud platforms and integration with Databricks.
• Experience with data modeling, dimensional modeling, and temporal data structures.
• Experience with CI/CD, DevOps, and infrastructure-as-code tools (Terraform, GitHub Actions, Azure DevOps).
• Knowledge of machine learning lifecycle, MLflow, and model deployment strategies.
• An understanding of E-R data models (conceptual, logical, and physical).
• Understanding of advanced data warehouse concepts is required
• Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions.
• Strong communication skills both verbal and written. Capable of collaborating effectively across a variety of IT and Business groups, across regions, roles and able to interact effectively with all levels.
• Strong problem-solving skills. Ability to identify where focus is needed and bring clarity to business objectives, requirements, and priorities.