IT Data Engineer

Novolex•Lake Forest, IL

10d

About The Position

We are seeking a highly motivated Data Engineer to join our Data & Analytics (D&A) organization. This role is ideal for a self-driven person who combines strong technical skills and analytical mindset with polished communication and collaboration skills. As a member of the Data and Analytics team, you will build innovative and scalable data products, and support analytics and reporting initiatives across the organization, including data needs in the Finance, Manufacturing, Supply Chain, and Commercial areas. The ideal candidate will have hands-on expertise in cloud data platforms like Azure/Microsoft Fabric or Databricks, strong experience with PySpark notebooks, data modeling skills, experience collaborating with business and technical teams, and have a focus on creating scalable, efficient, and actionable data products.

Requirements

Bachelor’s degree in Computer Science/MIS, Mathematics/Statistics, related disciplines, or equivalent technical work experience.
3+ years work experience designing, developing, and implementing data engineering solutions.
Hands-on experience with cloud data platforms (Azure Synapse, Azure Data Factory, Databricks) or Microsoft Fabric (Lakehouse, Pipelines, Dataflows, Notebooks), and modern ELT practices.
Strong expertise in PySpark, including writing and optimizing PySpark code inside notebooks (Azure Synapse, Databricks, or Microsoft Fabric).
Strong SQL and Python skills for data extraction, transformation, and analytics.
Familiarity with Delta Lake, Parquet, and distributed data processing patterns.
Understanding of data modeling, warehousing concepts, and data partitioning strategies.
Strong analytical mindset, ability to identify business insights from data, and creative problem-solving skills.
Proficient in documenting technical specifications, standard operating procedures, and support documentation using tools such as Visio and other Microsoft Office software.
Experience working in cross-functional teams and collaborating with business stakeholders.
Excellent communication and interpersonal skills to collaborate effectively with business stakeholders and other IT teams.
Ability and aptitude to evaluate and self-learn evolving technologies.
Relevant Microsoft or other certifications are highly desirable.

Nice To Haves

Proficiency in data visualization tools such as Microsoft Power BI.
Experience sourcing data from applications such as SAP, Blue Yonder, One Stream, etc. is desirable.
Experience with SAP ERP and its Data Model
Experience with an enterprise automation tool like Autosys
Experience with other ETL/ELT tools such as Alteryx
Familiarity with manufacturing, supply chain, or cost accounting processes.
Understanding of agile or iterative delivery methodologies.
Experience with machine learning and AI solutions is a plus.

Responsibilities

Data Modeling & Data Product Design: Translate business requirements into robust conceptual data models and data product designs to support easy and efficient analytics experience at all levels of the organization.
Create corresponding physical data models, data flow design, and technical specifications to enable building and implementation of the data product.
Data Product Development and Support: Bring data from disparate systems and applications into a central data lake/warehouse.
Collaborate with data analysts, data scientists, and engineering teams to deliver accessible, well-structured datasets.
Build scalable data models and storage layers using Azure Data Lake, Delta Lake, Synapse, Fabric Lakehouse, or related services.
Develop, optimize, and maintain PySpark notebooks for data processing, transformation, and analytics.
Design and manage ETL/ELT pipelines within Azure or Microsoft Fabric environments.
Create and maintain workflows using tools such as Azure Data Factory, Dataflow Gen2, Pipeline activities, or Fabric Data pipelines.
Set up orchestration of workflows using a mix of data platform options and an enterprise scheduler for cross-system dependencies.
Ensure high data quality, reliability, and performance across all data systems.
Maintain and Support Data Products: Document support documentation including standard operating procedures.
Monitor pipeline performance, troubleshoot failures, and optimize compute usage for cost efficiency.
Maintain data products and related analytics to meet analytics use case.
Business Insights and Dashboards: Design and create data visualizations and features that can power end-user analytics for actionable insights.
Engage in analysis of data to identify data insights that can aid business improvements.
Governance & Quality Document data sources, data definitions, and data lineage to ensure transparency and data governance.
Incorporate data quality processes into all data loads, and ensure alignment with enterprise governance standards.
Contribute to documentation, business glossaries, and data lineage tracking in the Alation data catalog.
Continuous Improvement Recommend and implement process enhancements that drive efficiency and data maturity.
Stay abreast of emerging tools and best practices in analytics and data management.