

Golden Technology
Sr Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Data Engineer with a contract length of "unknown", offering a pay rate of "unknown". Required skills include Azure Databricks, PySpark, and Delta Lake. Candidates should have 5+ years of data engineering experience and expertise in ETL solutions and DevOps practices.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
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ποΈ - Date
November 13, 2025
π - Duration
Unknown
-
ποΈ - Location
Unknown
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Cincinnati, OH
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π§ - Skills detailed
#Data Security #"ACID (Atomicity #Consistency #Isolation #Durability)" #Data Strategy #Data Engineering #Data Lineage #PySpark #Ansible #Scala #Delta Lake #Data Integration #Strategy #Documentation #Jenkins #SQL (Structured Query Language) #Azure #DevOps #"ETL (Extract #Transform #Load)" #Terraform #Data Pipeline #Security #Spark (Apache Spark) #Infrastructure as Code (IaC) #API (Application Programming Interface) #Automation #Azure Databricks #Databricks #Data Architecture
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
β’ Design, develop, and maintain data pipelines and ETL solutions in Azure Databricks using PySpark and Delta Lake.
β’ Implement data integration frameworks and API-based ingestion using tools like Apigee or Kong.
β’ Analyze, design, and deliver enterprise data architecture solutions focusing on scalability, performance, and governance.
β’ Implement automation tools and CI/CD pipelines using Jenkins, Ansible, or Terraform.
β’ Troubleshoot production failures and performance bottlenecks β fix partitioning, caching, shuffle, cluster sizing, and Z-ordering issues.
β’ Manage Unity Catalog, enforce data security (row/column-level access), and maintain data lineage.
β’ Administer Databricks clusters, jobs, and SQL warehouses, optimizing costs through auto-stop, job clusters, and Photon usage.
β’ Collaborate with cross-functional teams to drive data strategy and standards across domains.
β’ Create and maintain detailed architectural diagrams, interface specs, and data flow documentation.
β’ Mentor junior engineers on Databricks, Spark optimization, and Azure data best practices.
Required Skills & Experience
β’ 5+ years of experience as a Data Engineer with strong hands-on experience in Azure Databricks and PySpark.
β’ Solid understanding of Delta Lake, Z-ordering, partitioning, OPTIMIZE, and ACID transactions.
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
β’ Design, develop, and maintain data pipelines and ETL solutions in Azure Databricks using PySpark and Delta Lake.
β’ Implement data integration frameworks and API-based ingestion using tools like Apigee or Kong.
β’ Analyze, design, and deliver enterprise data architecture solutions focusing on scalability, performance, and governance.
β’ Implement automation tools and CI/CD pipelines using Jenkins, Ansible, or Terraform.
β’ Troubleshoot production failures and performance bottlenecks β fix partitioning, caching, shuffle, cluster sizing, and Z-ordering issues.
β’ Manage Unity Catalog, enforce data security (row/column-level access), and maintain data lineage.
β’ Administer Databricks clusters, jobs, and SQL warehouses, optimizing costs through auto-stop, job clusters, and Photon usage.
β’ Collaborate with cross-functional teams to drive data strategy and standards across domains.
β’ Create and maintain detailed architectural diagrams, interface specs, and data flow documentation.
β’ Mentor junior engineers on Databricks, Spark optimization, and Azure data best practices.
Required Skills & Experience
β’ 5+ years of experience as a Data Engineer with strong hands-on experience in Azure Databricks and PySpark.
β’ Solid understanding of Delta Lake, Z-ordering, partitioning, OPTIMIZE, and ACID transactions.






