Data Engineer

Description What Matters at Magid? YOU do!"The number one key to growth is having good people and that’s what has driven us at every stage of the game." - Greg Cohen, CEOAt Magid, we’re not just passionate about safety—we’re passionate about people. As an industry leader, we’ve built an innovative and collaborative environment where diversity is celebrated, ideas are valued, and personal and professional growth never stops.

Job Summary The Data Engineer plays a crucial, cross-functional role here s is a high-visibility role where your efforts will have impact on all levels of the organization. Our work spans product sourcing, customer journeys, service delivery, sales workflows, and the platforms and SME’s that support them. We have seen a drastic increase in adoption of the Data Engineer’s services. We are embedding data culture into our DNA and are excited to add a new face to that mission.

Essential Responsibilities Data pipelines and transformations (ingest, clean, vet, test, transform, publish)
Well-documented datasets and advanced semantic models that enable reporting and analysis

Data quality checks (freshness, completeness, validity) and participation in monitoring/alerting

Datasets that support machine learning use cases with clear definitions

Incremental improvements to pipeline performance, cost, and reliability with guidance

Collaboration with partners to clarify requirements and iterate on data products

Partner in Data Discovery & Solution Shaping Develop Power BI Solutions that are iterative while supporting our current ecosystem of analytics driven reporting

Learn source systems and data flows; help map entities, identifiers, and key business rules

Contribute to data modeling and design decisions with guidance (schemas, grain, slowly changing dimensions, etc.)Propose simpler, more reliable approaches (e.g., reuse shared datasets, standardize definitions) to improve trust and increase adoption

Build & Maintain Data Pipelines Build and maintain batch and/or streaming pipelines to ingest data from source systems into our analytical platform

Develop transformations to clean, standardize, and enrich data using agreed-upon patterns and tools (e.g., SQL, Python, Fabric Data Lake, KQL)
Support ML workflows by helping produce curated training datasets and feature-ready tables, following established patterns

Help monitor pipeline health and data quality; investigate variances and propose code enhancements to key datasets.

Contribute to a Strong Data Culture Help evolve data standards (naming conventions, modeling patterns, documentation) to improve consistency and reuse

Promote a culture of data trust through quality checks, clear definitions, and thoughtful change management

Willingness to tackle obscure requests and find ways to solve cumbersome outdated workflows

How We Work Empowered to solve problems, not just build features

Accountable for outcomes, not output

Collaborative by default, from discovery through delivery

Continuously learning, using data, AI/ML and customer insight to improve

Hybrid

Work Schedule:

Monday - Thursday onsite at our corporate office in Romeoville, IL;
Fridays WFH. Requirements Bachelor’s degree in Computer Science, Engineering, or a related field

Equivalent practical experience is equally valued

Strong SQL fundamentals (joins, aggregation, window functions, performance basics)
Data modeling mindset:
Cares about clear definitions, grain, and making data usable

Pragmatic problem solving:
Debugs issues, makes sensible tradeoffs, and knows when to ask for help Ownership:
Takes responsibility for assigned datasets/pipelines and follows through to production

Collaboration:

Works effectively with product managers to deliver trusted data

Key Qualifications Minimum of 5+ years of…