Golden Technology

Azure Data Engineer Level 3

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Azure Data Engineer Level 3, offering a contract length of "unknown" and a pay rate of "unknown." Key skills include Azure, Databricks, and Synapse expertise, with a focus on behavioral and Ecommerce data management. A minimum of 5 years' experience and relevant certifications are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 12, 2025
🕒 - 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
Sharonville, OH
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #SQL (Structured Query Language) #Microsoft Power BI #Compliance #Data Ingestion #Data Engineering #BI (Business Intelligence) #Jira #Agile #Delta Lake #Data Management #Azure Databricks #Data Processing #Alation #Synapse #Metadata #Data Science #Azure #Data Catalog #Datasets #Data Pipeline #Cloud #Data Architecture #Scala #ML (Machine Learning) #Data Mart #Databricks #Data Governance #Semantic Models #AI (Artificial Intelligence) #Data Transformations #Spark (Apache Spark) #Documentation
Role description
Job Description Position Overview • We are looking for a highly skilled, hands-on Senior Data Engineer to join our Data & Analytics team. • In this role, you will play a key part in building and scaling behavioral and Ecommerce data platform, enabling trusted analytics and making AI-ready data available across the organization. • You will be responsible for designing and implementing robust, scalable data pipelines, modeling complex, high-volume datasets, and delivering high-quality, well-structured data products to power business insights and future AI capabilities. • This is a delivery-focused engineering position demanding deep technical expertise in Azure, Databricks, and Synapse, combined with experience managing large-scale behavioral data in enterprise environments. Required Qualifications • 5+ years of experience in data engineering or similar roles, with hands-on delivery of cloud-based data solutions. • Preferred Engineering certifications: Microsoft Certified: Azure Data Engineer Associate and Databricks: Databricks Certified Data Engineer Professional • Strong expertise in Databricks and Azure Synapse, with practical experience in Spark-based data processing. • Proficient in modern data architectures (Lakehouse, ELT/ETL pipelines, real-time data processing). • Advanced SQL skills for data transformation and performance optimization. • Proven ability to model and manage large-scale, complex behavioral and Ecommerce datasets. • Expert in BI and best practices for data enablement and self-service analytics. • Hands-on experience with Unity Catalog and data cataloging tools (e.g., Alation) for governance and metadata management. • Working knowledge of behavioral analytics platforms (Adobe Analytics, Adobe Customer Journey Analytics). • Strong collaboration and communication skills • Experience operating in agile delivery environments, balancing speed, scalability, and solution quality. Key Responsibilities • Design, build, and maintain robust, scalable ELT/ETL pipelines and data transformations using Databricks, Spark, and Synapse. • Model high-volume, complex event-level datasets (digital behavior, Ecommerce transactions, marketing interactions) to support dashboards, experimentation, ML models, and marketing activation. • Enforce data governance, discoverability, and stewardship using Unity Catalog and Alation, ensuring compliance and lineage tracking. • Validate and reconcile data pipelines against established behavioral datasets such as Adobe Customer Journey Analytics (CJA) and Adobe Analytics. • Partner with data architects, analysts, data scientists, and marketing teams to deliver trusted, reusable, and well-structured datasets that power BI dashboards and decision-making. • Mature the data ingestion, processing, orchestration, and curation capabilities leveraging Delta Lake optimization, Databricks Workflows, and Synapse for analytical consumption. • Support and optimize semantic models and data marts that enable self-service analytics through AI/BI Dashboards and Power BI. • Participate in agile delivery processes (sprint planning, backlog refinement, documentation), collaborating through Jira and Confluence. • Document data assets, transformations, and pipelines for discoverability, transparency, and long-term maintainability.