Lead Databricks Engineer

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Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🏥 Healthcare

🏨 Hospitality

✈️ Travel

💰 $100M Private Equity Round on 2022-08

Healthcare • Hospitality • Travel

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• Design, develop, and maintain scalable data pipelines using Azure Databricks • Implement ETL/ELT workflows using PySpark, Spark SQL, and Python • Optimize Spark jobs for performance, cost, and scalability • Work with structured and semi-structured data (Parquet, Delta, JSON, CSV) • Build and manage Delta Lake tables, including ACID, time travel, and schema evolution • Integrate Databricks with Azure Data Lake Storage (ADLS Gen2) • Develop complex queries and transformations using SQL • Collaborate with data scientists, analysts, and stakeholders to support analytics and ML use cases • Ensure data quality, validation, and monitoring • Follow best practices for security, access control, and governance in Azure

🎯 Requirements

• 6+ years of experience in Data Engineering • Strong hands-on experience with Azure Databricks • Proficiency in Python for data processing • Strong knowledge of SQL, including joins, window functions, and performance tuning • Hands-on experience with Apache Spark / PySpark • Experience working with Delta Lake • Knowledge of Azure Data Lake Storage (ADLS Gen2) • Understanding of distributed computing concepts • Experience with Git version control • Experience with Azure Data Factory • Exposure to CI/CD pipelines, including Azure DevOps and GitHub Actions • Basic understanding of data modeling • Familiarity with cloud security and RBAC in Azure • Exposure to streaming data, including Spark Structured Streaming, Event Hub, and Kafka