Technical Architect-Datawarehousing

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.

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., Bachelors, Qualifications : BACHELOR OF COMPUTER SCIENCE You must create an Indeed account before continuing to the company website to apply