Lead, IT Data Engineer

Shure•Niles, IL

11d•Hybrid

About The Position

Come join the global IT team at Shure! In your role as Lead Data Engineer, you will play a critical role in enabling Shure’s global analytics and data strategy. This position partners closely with business and technology stakeholders across North America, Europe, and Asia to design, build, enhance, and support scalable analytics solutions that meet evolving global business needs. In this senior role, you’ll be responsible for engineering and supporting robust data pipelines that leverage Shure’s technology investments and enable insights across the organization. You’ll work with a wide variety of data sources—including structured and unstructured data, internal and external data, and emerging data types such as Internet of Things (IoT)—to ensure data is reliable, accessible, and optimized for analytics and reporting. The ideal candidate brings a strong foundation in data engineering best practices, stays current with technology trends, and demonstrates a willingness to learn and adopt emerging tools and platforms. Success in this role requires both technical depth and the ability to collaborate effectively within a globally distributed team to deliver high‑quality, business‑driven data solutions. This role is hybrid, based in our Niles, IL location or remote within the US.

Requirements

Demonstrated commitment to working in alignment with Shure’s core values, fostering collaboration, integrity, innovation, and excellence in all deliverables.
Minimum of 10 years of related experience with a Bachelor’s degree; or 8 years with a Master’s; or 5 years with a PhD; or equivalent experience in enterprise data warehouse/data lake platforms and big data technologies.
Strong professional judgment, problem-solving, and communication skills to analyze complex data challenges and deliver well-structured solutions.
Expertise across end-to-end data processes, including application integration touchpoints and alignment of local/global requirements.
Hands-on experience with AWS Data Engineering stack (S3, Glue, Lambda, EMR/Spark, Step Functions, Athena, Lake Formation, IAM, Redshift).
Advanced proficiency in Snowflake (data modeling, performance tuning, Snowpipe, Streams/Tasks, RBAC, cost governance, query optimization).
Skilled in designing and implementing CI/CD pipelines for data engineering workflows using GitLab, GitHub Actions, Azure DevOps, Terraform/CDK, and dbt.
Experience integrating ERP (SAP, Oracle) and CRM (Salesforce) data into cloud platforms.
Knowledge of structured/unstructured data and integration protocols (OData, ODP, REST APIs, JDBC/ODBC, file-based, custom interfaces).
Strong understanding of modern data architecture patterns (Medallion, Lambda, Kappa, Data Mesh), dimensional and Data Vault modeling, and data quality methods.
Expertise in SQL, shell scripting, Python or PySpark for data engineering and automation.
Familiarity with Machine Learning concepts, Generative AI, and enabling ML pipelines and feature stores.
Experience with real-time streaming technologies (Apache Kafka, AWS Kinesis, MSK) for high-throughput, low-latency pipelines.
Knowledge of data visualization tools (Tableau, Power BI) and project management methodologies (SAFe Agile, Waterfall).
Ability to rapidly learn new technologies and convert business requirements into technical designs.

Responsibilities

Lead and perform data engineering development for connecting source systems to Shure’s data lake, ensuring data quality and governance standards.
Assist internal business partners in implementing Generative AI-driven analytics solutions, providing guidance on use cases, integration strategies, and best practices to enhance data insights and decision-making.
Collaborate with business partners to define analytic use cases, develop business cases, and ensure benefits realization through measurable outcomes and value delivery.
Design and implement ETL processes to extract, transform, and load data from multiple sources into Shure’s data lake and data warehouse.
Develop and maintain scalable, flexible data models and analytic solutions aligned with business requirements.
Drive technical solution design and provide approvals for documentation, proposals, and final designs.
Establish and maintain data lineage and cataloging to enable discoverability and support governance initiatives.
Oversee code reviews, testing, and validation to ensure high-quality deliverables and adherence to standards.
Provide technical leadership and mentorship to data engineers, serving as the first escalation point for complex issues.
Collaborate with cross-functional teams and external contacts, offering thought leadership on emerging technologies and trends.
Manage medium to large-scope projects, including planning, resource allocation, and execution of technical phases while supporting business users through Service Desk requests.
Lead continuous improvement initiatives, including automation, monitoring, and reliability enhancements for the data platform.