Azure Data Engineer

Freudenberg Group • Plymouth, MI

18h

About The Position

Working at Freudenberg: We will wow your world! Responsibilities: Design and Build Data Pipelines: Develop, implement, and maintain robust, scalable data pipelines and ETL processes to integrate data from diverse sources. Cloud Data Infrastructure: Collaborate with IT and business teams to set up and optimize advanced cloud-based data infrastructure, supporting AI-driven models and analytics. Data Transformation & Modeling: Create algorithms and data models to convert raw data into actionable insights, aligning with business objectives. Data Quality & Security: Ensure data integrity, quality, and security across all systems, implementing validation, backup, recovery, and disaster recovery plans. Pipeline Optimization: Continuously evaluate and enhance data systems and processes for improved efficiency, reliability, and performance (including query tuning and indexing). Migration & Modernization: Lead migration of on-premises data systems to cloud solutions, focusing on Azure and modern data architectures (e.g., real-time processing, data warehousing). Collaboration: Work closely with data scientists, analysts, and other stakeholders to meet organizational data needs and drive strategic data management projects The Freudenberg Group is an equal opportunity employer that is committed to diversity and inclusion. Employment opportunities are available to all applicants and associates without regard to race, color, religion, creed, gender (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity or expression, national origin, ancestry, age, mental or physical disability, genetic information, marital status, familial status, sexual orientation, protected military or veteran status, or any other characteristic protected by applicable law. Freudenberg-NOK General Partnership Welcome to Freudenberg Without Freudenberg, indoor air would not be as clean, cars would not drive and wounds would not heal as quickly. And these are just three examples from thousands of our applications. Working at Freudenberg: "We will wow your world!" This is our promise. As a global technology group, we not only make the world cleaner, healthier and more comfortable, but also offer our 51,000 employees a networked and diverse environment where everyone can thrive individually. Be surprised and experience your own wow moments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Proficiency in Python and SQL; experience with both relational and non-relational databases (MS SQL, Azure SQL Database).
• Hands-on experience with Databricks, Azure Data Factory, and modern data warehouse tools.
• Strong understanding of data security, backup, and recovery best practices.
• Knowledge of cloud infrastructure management, particularly on the Azure platform.
• Communicates clearly and concisely, while serving as a sparring partner to internal/external stakeholders.
• Fosters teamwork between employees and across the organization.
• Drives a customer-oriented business strategy and provides indispensable support to deliver successful outcomes.
• Envisions the impact of potential future trends and proactively drives necessary changes.
• Encourages creativity and initiative from employees.
• Inspires and motivates self and others, while taking full accountability for actions and results.

Nice To Haves

• Familiarity with real-time data processing tools (e.g., Kafka, Flink) is a plus.
• Experience with CI/CD pipelines, automation for data deployments, and infrastructure as code (e.g., Terraform).
• Experience in automotive and/or chemical data domains is a plus.

Responsibilities

• Design and Build Data Pipelines: Develop, implement, and maintain robust, scalable data pipelines and ETL processes to integrate data from diverse sources.
• Cloud Data Infrastructure: Collaborate with IT and business teams to set up and optimize advanced cloud-based data infrastructure, supporting AI-driven models and analytics.
• Data Transformation & Modeling: Create algorithms and data models to convert raw data into actionable insights, aligning with business objectives.
• Data Quality & Security: Ensure data integrity, quality, and security across all systems, implementing validation, backup, recovery, and disaster recovery plans.
• Pipeline Optimization: Continuously evaluate and enhance data systems and processes for improved efficiency, reliability, and performance (including query tuning and indexing).
• Migration & Modernization: Lead migration of on-premises data systems to cloud solutions, focusing on Azure and modern data architectures (e.g., real-time processing, data warehousing).
• Collaboration: Work closely with data scientists, analysts, and other stakeholders to meet organizational data needs and drive strategic data management projects

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level