Lead Data Engineer; Databricks, Big Data)

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Norfolk Southern offers a unique opportunity to be part of our proud legacy that spans nearly 200 years. We are a customer-centric, operations-driven team dedicated to advancing safety, serving communities, and driving innovation for tomorrow's rail. As part of Norfolk Southern, you’ll join a collaborative team where there are opportunities for growth across the organization. We are building a culture where everyone can thrive by owning and driving exceptional results, being humble and leading with trust, serving our customers with excellence, and collaborating and coaching to win.

Norfolk Southern Corporation is seeking a Lead Data Engineer who enjoys collaborating across the organization to deliver reliable, scalable data solutions. Join a skilled team focused on modern data platforms, where you will lead the definition of architecture, help shape and operate our Databricks-based lakehouse and streaming analytics capabilities, and guide the team through technical delivery.

This role blends strong business and analytical judgment with hands-on engineering and technical leadership: you will partner with stakeholders and the engineering team to understand problems, translate them into clear requirements, define and drive pragmatic architectures, and deliver production-grade ingestion and transformation pipelines - with ownership through deployment and steady-state operations. You will also work closely with the team to proactively identify and remove technical blockers that stand in the way of delivery.

In this role, you will work with teams across the company to clarify Data and Analytics needs, perform structured requirements discovery alongside Data Modelers, align with BI development on scope and estimates, and lead and guide delivery through completion while promoting engineering quality, consistency, and best practices across the team.

• Lead the definition of data architecture in partnership with the team and stakeholders, setting technical direction for the lakehouse, ingestion, and transformation patterns.
• Identify, escalation, and remove technical blockers for the team - unblocking delivery through hands-on problem solving, design decisions, or coordination with other teams.
• Lead the design and development of enterprise data models (conceptual, logical, and physical) across domains, ensuring they align with lakehouse and pipeline architecture.
• Define and enforce data modeling standards, best practices, and governance processes, leveraging tools such as Erwin.
• Define data requirements, gather, and wrangle large scale of structured and unstructured data, and validate data by running various data tools in the Data Environment.
• Support the standardization, customization and ad-hoc data analysis, and will develop the mechanisms to ingest, analyze, validate, normalize and clean data.
• Create data policy and develop interfaces and retention models which require synthesizing or anonymizing data.
• Implement statistical data quality procedures on new data sources, and by applying rigorous iterative data analytics, supports Data Scientists and analytics and insights creation in data sourcing and preparation to visualize data and synthesize insights of commercial value.
• Develops and maintains…