Technical Architect-Datawarehousing

Databricks Architect


Must Have Technical/Functional Skills


Experience: 5+ years of hands-on data engineering experience, with at least 3 years focused on the Databricks/Spark


Ecosystem


Databricks Expertise: Deep, hands-on expertise with the Databricks Lakehouse Platform, including Delta Lake,


Structured Streaming, Delta Live Tables, and cluster configuration/optimization.


Programming Mastery: Expert-level proficiency in Python and PySpark. Advanced SQL skills are essential.


Data Warehousing Concepts: Strong understanding of data modeling principles, including dimensional modeling


(Kimball), data warehousing concepts, and ETL/ELT design patterns.


Cloud Proficiency: Proven experience working with a major cloud provider (Azure, AWS, or GCP), particularly with


data storage S3 and related services.


Software Engineering Mindset: Experience with software engineering best practices, including version control (Git),


code reviews, testing, and CI/CD.

Roles and Responsibilities


Data Pipeline Development: Design, code, and deploy robust and scalable batch and streaming data pipelines


using PySpark, Spark SQL, and Delta Live Tables to ingest data from sources such as Point-of-Sale (POS), e-commerce


platforms, loyalty systems, and marketing clouds.


Data Modeling and Transformation: Implement complex data transformations and business logic within the Medallion


architecture (Bronze, Silver, Gold layers). Build and optimize the final "Gold" customer-dimension tables that will


serve as the single source of truth.


Data Quality: Implement data quality frameworks and cleansing routines to ensure the accuracy and trustworthiness


of the Customer 360 data.


Performance Optimization: Proactively monitor, debug, and tune Databricks jobs and Spark clusters for performance


and cost-efficiency. Implement best practices for partitioning, caching, and data layout in Delta Lake.


Infrastructure as Code (IaC) & CI/CD: Work with DevOps teams to manage Databricks environments, clusters, and


job deployments using tools like Terraform and AWS DevOps/GitHub Actions. Champion and implement CI/CD best


practices for data pipelines.


Data Governance and Security: Implement data governance features within Databricks Unity Catalog, including


data lineage tracking, access controls, and data masking to ensure compliance and security.


Collaboration: Partner closely with Functional Consultants, Data Scientists, and Analytics Engineers to understand


their data requirements and deliver well-structured, consumption-ready datasets.


Education


Bachelors

Salary Range: $120000 - $150000 a year