Job Description Data Engineering for Mfg and MAKE program – taking legacy systems/data and building up environments/set up/data modeling/repositories to shift to new ERP solution M3 (Infor Product). Data needs, with procurement, flows, etc. Accountable for developing and delivering technological responses to targeted business outcomes. Analyze, design and develop enterprise data and information architecture deliverables, focusing on data as an asset for the enterprise. Understand and follow reusable standards, design patterns, guidelines, and configurations to deliver valuable data and information across the enterprise, including direct collaboration with & other Data Engineer groups within , where needed. Demonstrate the company's core values of respect, honesty, integrity, diversity, inclusion and safety. Responsibilities • Utilize enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses • Ensure there is clarity between ongoing projects, escalating when necessary, including direct collaboration with & other Data Engineering groups within , plus working with vendor partners that currently staff data engineers and our data team. • Leverage innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms • Define high-level migration plans to address the gaps between the current and future state • Contribute to the development of cost/benefit analysis for leadership to shape sound architectural decisions • Analyze technology environments to detect critical deficiencies and recommend solutions for improvement • Promote the reuse of data assets, including the management of the data catalog for reference • Be instrumental in tool assessment, recommending, deploying, support around data extraction from source systems, cleansing, converting to M3 platform/cloud solutions, etc on the work we are doing; to help us mature and grow how we can systematically get better and faster using tool sets to do this work long term. • Draft architectural diagrams, interface specifications and other design documents • Must be able to perform the essential job functions of this position with or without reasonable accommodation Deep knowledge and ability to build data models, pipelines in data engineering, Databricks knowledge and hands on building/executing, AWS/Azure or cloud environments, how to apply on new ERP solutions and rollouts, ability to work in legacy systems with data models, moving to new solutions and ERPs. Qualifications Minimum • Bachelor's Degree computer science, software engineering, or related field • Any experience in a minimum of two of the following technical disciplines: data warehousing, big data management, analytics development, data science, application programming interfaces (APIs), data integration, cloud, servers and storage, and database mgmt • 4+ years successful and applicable experience building complex data solutions that have been successfully delivered to customers • 4+ years proven track record of delivering large scale, high quality operational or analytical data systems • 4+ years experience in the data development and principles including end-to-end design patterns • Excellent oral/written communication skills Desired • Any experience with SSAS Tabular models, Power BI, Dataflows and DAX • Any experience building solutions using elastic architectures (preferably Microsoft Azure and Google Cloud Platform) • Any experience with a variety of SQL, NoSQL and Big Data Platforms • Any experience with data science solutions or platforms • Any experience with streaming technologies like Kafka, IBM MQ and EventHub • Any experience with Python, Spark and SQL • Any experience with Azure Data Platform stack: Azure Data Lake, Data Factory and Databricks Python, Pyspark, SQL, Azure Databricks, Unity Catalog, EventHub, ADF, Synapse, FunctionAPP, AWS, Infor M3 and Birst Analytics, Data Modeling, DBA Admin, IDE development Key Responsibilities • Utilize enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses • Ensure there is clarity between ongoing projects, escalating when necessary, including direct collaboration with & other Data Engineering groups within , plus working with vendor partners that currently staff data engineers and our data team. • Leverage innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms • Define high-level migration plans to address the gaps between the current and future state • Contribute to the development of cost/benefit analysis for leadership to shape sound architectural decisions • Analyze technology environments to detect critical deficiencies and recommend solutions for improvement • Promote the reuse of data assets, including the management of the data catalog for reference • Be instrumental in tool assessment, recommending, deploying, support around data extraction from source systems, cleansing, converting to M3 platform/cloud solutions, etc on the work we are doing; to help us mature and grow how we can systematically get better and faster using tool sets to do this work long term. • Draft architectural diagrams, interface specifications and other design documents • Must be able to perform the essential job functions of this position with or without reasonable accommodation • Deep knowledge and ability to build data models, pipelines in data engineering, Databricks knowledge and hands on building/executing, AWS/Azure or cloud environments, how to apply on new ERP solutions and rollouts, ability to work in legacy systems with data models, moving to new solutions and ERPs.