Azure Data Engineer Databricks

Develop production-grade data engineering solutions based on solution designs provided by Senior Data Engineers. Build and maintain end-to-end data pipelines from ingestion through visualization. Implement data ingestion using batch, CDC, streaming, and API integration patterns. Design and develop physical data models in Snowflake and Databricks. Work with Delta Lake, Unity Catalog, Iceberg Tables, and Medallion Architecture (Bronze, Silver, Gold). Develop semantic layer components in Microsoft Fabric (OneLake, Fabric IQ). Build Power BI dashboards, reports, and visualizations. Implement unit testing, integration testing, data quality validation, reconciliation checks, and SLA monitoring. Support production pipelines and provide KTLO (Keep The Lights On) support. Maintain technical documentation, lineage, mappings, runbooks, and data dictionaries. Follow DevOps best practices including Git, CI/CD, code reviews, and automated testing. Participate in stakeholder discussions and technical design reviews. Collaborate with engineering teams and contribute to knowledge-sharing initiatives.

Preferred Background Candidates with Full time experience from any of the following organizations are highly preferred: Google, Meta, Amazon, Apple, Netflix, Microsoft, Nvidia, Salesforce, Oracle, IBM, Intel, Cisco, Adobe, Palantir, Snowflake, Databricks, X (Twitter), LinkedIn, Uber, Airbnb

Mandatory Skills Required Experience

Microsoft Fabric 4+ Years Data Engineering 4+ Years Databricks 4+ Years Python 4+ Years Snowflake 4+ Years, Bachelor's Degree in Computer Science, Information Systems, Software Engineering, or equivalent experience. 4+ years of hands-on Data Engineering experience in enterprise environments. Strong SQL and Python development experience. Hands-on expertise with: o Databricks o Delta Lake o Unity Catalog o PySpark o Spark SQL o Snowflake Experience with Microsoft Fabric and OneLake. Experience developing Power BI reports and dashboards. Knowledge of: o Data Modeling o Lakehouse Architecture o Dimensional Modeling o Data Quality Frameworks o Pipeline Testing Experience with Git, CI/CD, and DevOps methodologies. Strong communication and stakeholder management skills. Preferred Qualifications Experience with Iceberg Tables or modern open table formats. HR Analytics and People Analytics domain experience. Experience with Workday, ServiceNow HR, or similar HR platforms. Exposure to: o Kafka o Azure Event Hub o Delta Live Tables o Spark Structured Streaming Experience supporting AI/ML workloads. Familiarity with: o Teradata o Oracle o SQL Server Azure Certifications preferred. Knowledge of enterprise lakehouse architectures and data governance. Understanding of GDPR, CCPA, and employee data privacy regulations.