Lead Data Engineer: Lakehouse & Streaming Architect

Norfolk Southern Corp.

Atlanta (GA)

Hybrid

USD 140,000 - 180,000

Full time

11 hours ago
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Job summary

Norfolk Southern Corporation in Atlanta, GA is seeking a Lead Data Engineer to drive the definition of data architecture and operate our lakehouse and streaming analytics capabilities. You will guide the team through end-to-end delivery, collaborating with stakeholders to translate needs into pragmatic, production-grade pipelines.

You will partner with data science and BI teams to develop scalable models, ensure data quality, and promote engineering best practices across the organization.

Qualifications

  • Databricks Lakehouse expertise with 10+ years in data engineering.
  • Experience with Spark/PySpark and Delta Lake.
  • Kafka (Confluent) and AWS cloud analytics services experience.
  • Strong data modeling and SQL skills with governance.
  • Technical leadership and cross-team collaboration.

Responsibilities

  • Lead data architecture for lakehouse, ingestion, and transformation.
  • Unblock delivery by solving blockers and coordinating with teams.
  • Design enterprise data models across domains aligning with pipelines.
  • Define data standards, governance, and modeling practices (Erwin).
  • Develop data pipelines to ingest, transform, and validate data.
  • Collaborate with data science and BI teams on models.

Skills

Databricks Lakehouse
Streaming & Cloud Infra
Data Modeling & SQL
Technical Leadership
Delivery & Collaboration

Education

Bachelor's Degree

Tools

Databricks
Spark/PySpark
Delta Lake
Unity Catalog
Erwin
Kafka
AWS

Job description

Norfolk Southern Corporation in Atlanta, GA is seeking a Lead Data Engineer to drive the definition of data architecture and operate our lakehouse and streaming analytics capabilities. You will guide the team through end-to-end delivery, collaborating with stakeholders to translate needs into pragmatic, production-grade pipelines.

You will partner with data science and BI teams to develop scalable models, ensure data quality, and promote engineering best practices across the organization.

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