Manager Data Engineer

Manger Data Engineer

Department: Data & Analytics
Reports To: Director, Data Engineering
Location: Remote (U.S.)Position Summary the company is seeking an experienced Lead Data Engineer to help shape the future of our enterprise data platform and AI strategy. This is a highly visible technical leadership role responsible for architecting, building, and evolving our modern cloud data platform while establishing engineering standards, mentoring a growing team, and driving innovation across the organization.

As a Lead Data Engineer, you will serve as the technical leader for our Databricks Lakehouse platform, providing hands-on leadership across data ingestion, transformation, governance, analytics enablement, and AI-ready data products. You will partner closely with Business Intelligence, Product, Platform Engineering, Security, Data Governance, and MLOps teams to build trusted, scalable, and governed data solutions that power enterprise analytics, machine learning, and generative AI.This

role combines deep technical expertise with leadership, mentoring, and strategic influence. You'll help establish the long-term technical direction of the company's data ecosystem while coaching and developing engineers, driving engineering excellence, and implementing modern data engineering best practices.

the company is in the midst of an exciting enterprise-wide data platform modernization journey. We are investing in a modern cloud-native architecture built on Databricks, Azure, and AI-enabled technologies that will become the foundation for analytics, operational reporting, machine learning, and generative AI across the company.

This is a unique opportunity to join at a transformational point in our technology journey. Rather than simply maintaining existing systems, you'll help define the future of our data platform—shaping architecture, engineering standards, governance, and the adoption of emerging AI technologies that will influence how data is used across the organization for years to come. You will also be a key player in our drive for Self Service Analytics at PFG.

• Help define the long-term strategy for the company's modern Data & AI platform.
• Influence enterprise architecture decisions around Databricks, Azure, Unity Catalog, semantic data products, and AI-powered analytics.
• Build modern, scalable data products that enable self-service analytics and generative AI.
• Lead adoption of emerging Databricks capabilities, including Genie, AI/BI, Unity Catalog, Lakeflow, and other evolving platform innovations.
• Mentor and develop a growing Data Engineering team while establishing engineering standards that scale across the organization.
• Partner directly with technology and business leaders to solve meaningful business problems using modern cloud and AI technologies.

• Provide technical leadership for the Data Engineering team through architecture guidance, code reviews, mentoring, and engineering best practices.
• Mentor and develop junior and mid-level Data Engineers, fostering technical growth, knowledge sharing, and continuous learning.
• Establish engineering standards for software development, testing, CI/CD, documentation, observability, and operational excellence.
• Lead technical design discussions, evaluate architectural tradeoffs, and drive adoption of modern engineering practices.
• Champion a culture of quality, collaboration, innovation, and continuous improvement.

• Serve as the technical lead for the company's Databricks Lakehouse platform.
• Design, build, and support scalable enterprise data pipelines using SQL, Python, Apache Spark, and Databricks.
• Define best practices for Databricks development, including Workflows, Repos, Jobs, notebooks, reusable Python libraries, Git integration, cluster policies, SQL Warehouses, and deployment automation.
• Design and optimize Delta Lake architectures using Medallion patterns, Delta optimization, Liquid Clustering, and Photon.
• Build reusable ingestion frameworks supporting batch, streaming, CDC, and API-based integration…