Job Description

Top 3 skills: Azure, Databricks, Azure Data Factory, Synapse, Azure Data Lake Storage, Python & PySpark, SQL

Soft Skills Needed: Very good communication, able to own or take responsibility of tasks with minimal assistance, strong collaboration with multiple stakeholders

Project person will be supporting: Supply Chain Data Engineering Team shared services team

Team details ie. size, dynamics, locations: Around 10 people, mix of FTE and contractors, onsite and offshore

Work Location (in office, hybrid, remote): Cincinnati locals (onsite twice a week) only Local s

We are seeking a highly skilled Senior Azure Data Engineer to join our growing data team. In this role, you will be responsible for designing, building, and optimizing scalable data pipelines and architectures using Microsoft Azure services. You will collaborate closely with data scientists, analysts, and business stakeholders to ensure data is accessible, reliable, and efficiently processed.

Requirements

• 5+ years of experience in data engineering or a related field
• 2+ years of hands-on experience with Azure cloud technologies
• Deep experience with Azure Data Factory, Databricks, Azure Synapse, and Azure Data Lake Storage
• Proficient in Python and PySpark for data processing and transformation
• Strong SQL skills and solid understanding of data modeling principles
• Good understanding of cloud architecture, data warehousing concepts, and distributed systems
• Excellent communication skills and the ability to collaborate effectively with multiple stakeholders
• Ability to take ownership of tasks with minimal assistance

Nice to Have

• Experience with DevOps practices, CI/CD pipelines, and version control tools like Git
• Background in building scalable data pipelines in enterprise environments
• Experience working in cross-functional Agile teams

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes using Azure Data Factory, Databricks, and PySpark
• Architect and implement cloud-based data solutions on Azure, utilizing services such as Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL
• Develop and optimize complex SQL queries and stored procedures to support data transformation and reporting needs
• Work with both structured and unstructured data to build clean, reusable datasets for analytics and business intelligence
• Monitor, troubleshoot, and enhance the performance, reliability, and efficiency of data workflows and pipelines
• Ensure adherence to data quality, governance, and security standards across all data processes and environments
• Collaborate with data scientists and analysts to support machine learning and artificial intelligence initiatives
• Contribute to the development of best practices, maintain documentation, and promote knowledge sharing within the data engineering team

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