Golden Technology

Sr Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Data Engineer with a contract length of "unknown" and a pay rate of "$/hour". It requires 5+ years of experience in Azure Databricks and PySpark, focusing on data pipeline development, Delta Lake management, and DevOps practices.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 7, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Cincinnati Metropolitan Area
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🧠 - Skills detailed
#Delta Lake #Data Security #Automation #"ETL (Extract #Transform #Load)" #Data Integration #API (Application Programming Interface) #Security #SQL (Structured Query Language) #Terraform #Data Architecture #Azure Databricks #Data Engineering #Data Lineage #"ACID (Atomicity #Consistency #Isolation #Durability)" #Documentation #Strategy #Data Strategy #Data Pipeline #Azure #Ansible #Jenkins #Scala #Infrastructure as Code (IaC) #DevOps #Databricks #PySpark #Spark (Apache Spark)
Role description
We are seeking a Senior Databricks Engineer with deep hands-on experience designing and implementing large-scale data solutions on Azure Databricks. The ideal candidate has real-world experience building and troubleshooting production-grade data pipelines, optimizing Spark workloads, managing Delta Lake architecture, and implementing DevOps best practices using IaC and CI/CD automation. Key Responsibilities • Design, develop, and maintain data pipelines and ETL solutions in Azure Databricks using PySpark and Delta Lake. • Implement data integration frameworks and API-based ingestion using tools like Apigee or Kong. • Analyze, design, and deliver enterprise data architecture solutions focusing on scalability, performance, and governance. • Implement automation tools and CI/CD pipelines using Jenkins, Ansible, or Terraform. • Troubleshoot production failures and performance bottlenecks — fix partitioning, caching, shuffle, cluster sizing, and Z-ordering issues. • Manage Unity Catalog, enforce data security (row/column-level access), and maintain data lineage. • Administer Databricks clusters, jobs, and SQL warehouses, optimizing costs through auto-stop, job clusters, and Photon usage. • Collaborate with cross-functional teams to drive data strategy and standards across domains. • Create and maintain detailed architectural diagrams, interface specs, and data flow documentation. • Mentor junior engineers on Databricks, Spark optimization, and Azure data best practices. Required Skills & Experience • 5+ years of experience as a Data Engineer with strong hands-on experience in Azure Databricks and PySpark. • Solid understanding of Delta Lake, Z-ordering, partitioning, OPTIMIZE, and ACID transactions.