Data Engineering and Analytics Manager

Corning•Village of Fairport, NY

8d•$126,898 - $174,486

About The Position

The Division Data Engineering and Analytics Manager is responsible for leading the design, delivery, and ongoing improvement of the division’s data engineering and analytics foundation. This role will oversee the development and support of scalable data pipelines, cloud-based data platforms, and curated data assets that enable trusted reporting, analytics, and future advanced analytics use cases. This leader will play a critical role in stabilizing and maturing the current data engineering and Databricks environment, establishing delivery standards, and strengthening the data foundation needed to support business insights and decision-making. The role will also help shape and enable broader analytics capabilities by partnering with business, functional, and technology teams to ensure data is reliable, governed, and fit for use. The ideal candidate combines strong data engineering and platform experience with people leadership, delivery discipline, and an understanding of how data supports analytics, business performance, and future advanced analytics opportunities. This role reports to the Senior Manager, Division Data & Analytics (Division Data Office) and works closely with business stakeholders, functional partners, enterprise IT, analytics teams, and data governance partners.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or related field.
5+ years of experience in data engineering, data integration, analytics engineering, or related data platform roles.
2+ years of experience leading teams, projects, or delivery efforts in a data and analytics environment.
Hands-on experience with modern data platforms and cloud-based data engineering solutions, including Databricks or similar technologies.
Strong experience in designing, building, and supporting data pipelines, ETL/ELT processes, and curated data models.
Experience with SQL and one or more programming/scripting languages such as Python, Scala, or similar.
Experience working with BI, reporting, or analytics teams to support trusted data consumption.
Strong understanding of data quality, governance, controls, and metadata/lineage concepts.
Demonstrated ability to work across business and technology teams and communicate effectively with technical and non-technical stakeholders.

Nice To Haves

Experience in manufacturing, supply chain, operations, finance, or other complex enterprise environments.
Experience with cloud data ecosystems such as Azure, AWS, or GCP.
Familiarity with advanced analytics, machine learning, or AI data preparation requirements.
Experience supporting enterprise-scale reporting and dashboard environments.
Experience implementing or supporting data governance practices and operating models.
Knowledge of DevOps, DataOps, CI/CD, and automated testing practices for data pipelines.

Responsibilities

Lead the day-to-day management, support, and enhancement of the division’s data engineering environment, including Databricks and related data platform capabilities.
Build and maintain curated, trusted, and reusable data assets that support reporting, dashboards, self-service analytics, and business intelligence.
Lead, coach, and develop data engineering resources, including internal team members and partners as applicable.
Drive platform data governance partnering with business, and functional stakeholders to improve data quality, lineage, controls, and ownership across the data lifecycle.
Help build the data foundation required to support future advanced analytics, data science, and AI use cases.