Principal Data Engineer

Oshkosh Corporation•Oshkosh, WI

About The Position

At Oshkosh, we build, serve and protect people and communities around the world by designing and manufacturing some of the toughest specialty trucks and access equipment. We employ over 18,000 team members all united by a common purpose. Our engineering and product innovation help keep soldiers and firefighters safe, is critical in building and keeping communities clean and helps people do their jobs every day. SUMMARY: As a member of the Advanced Analytics organization, your primary responsibilities will be to support comprehensive planning and execution in providing a world-class set of capabilities around data ingestion and transformation, as well as analytics platform and solutions architecture. YOUR IMPACT: Plan, architect, design and develop scalable data and analytics solutions to deliver quantifiable value to our business teams. Own the architecture and user access patterns for analytics and data platforms. Collaborate with cross-functional teams (e.g. data engineers, data analysts, scientists, architects, business stakeholders, application owners) on analytics product development and data requirements. Provide guidance and leadership for end-to-end testing, system integration testing, and validation to support the accuracy of data transformations and data verifications used. Possesses extensive understanding of ETL pipelines, SQL, programming, relational databases, data modeling, transactional and BI databases, and networking. Significant experience with tools such as Terraform, Spark, Databricks, Snowflake, Git, and Azure infrastructure management (ADLS Gen2, Azure Compute, Azure Data Factory, AI Foundry, AKS, VPC’s, Storage Accounts, and others). Build and maintain documentation, such as version-controlled work instructions, detailed design documents and architecture documentation. Direct data engineering assignments, job scheduling, performance-tuning data processes, and troubleshooting data processing issues (including root cause resolution). Set standards for data governance (quality, security, etc.) within the Azure data lake. Familiarity with ITIL methodology and ticketing software to track and manage incidents, changes, problems, tasks, and demand. Lead coaching and mentoring and serve as a Subject Matter Expert (SME) on new technologies and best practices across data engineering (i.e. data modeling, database design, ETL design, job scheduling and monitoring, etc.) Possesses advanced understanding of data structure, data processing, and overall landscape of source/ERP systems. Possesses strong critical thinking, analytical, problem-solving, organizational, multitasking, interpersonal, and presentation skills. Designs the strategic roadmap and forward analysis for data engineering, including proof of concepts and vendor management. Direct feasibility studies and project estimates for proposed projects. Analyzes trends, emerging technologies, and version updates to optimize data engineering's vendor relationships, technical solutions, and improve customer experience. Partners across technology SMEs for process, policy, and procedure best practices and design. Proficiency in Excel skills and programming skills Develop process improvement strategies based on pattern recognition with the business for proactive solutions.

Requirements

Possesses extensive understanding of ETL pipelines, SQL, programming, relational databases, data modeling, transactional and BI databases, and networking.
Significant experience with tools such as Terraform, Spark, Databricks, Snowflake, Git, and Azure infrastructure management (ADLS Gen2, Azure Compute, Azure Data Factory, AI Foundry, AKS, VPC’s, Storage Accounts, and others).
Familiarity with ITIL methodology and ticketing software to track and manage incidents, changes, problems, tasks, and demand.
Possesses advanced understanding of data structure, data processing, and overall landscape of source/ERP systems.
Possesses strong critical thinking, analytical, problem-solving, organizational, multitasking, interpersonal, and presentation skills.
Proficiency in Excel skills and programming skills
Bachelors degree with seven (7) or more years of experience in the field or in a related area.

Nice To Haves

Masters or doctorate degree

Responsibilities

Plan, architect, design and develop scalable data and analytics solutions to deliver quantifiable value to our business teams.
Own the architecture and user access patterns for analytics and data platforms.
Collaborate with cross-functional teams (e.g. data engineers, data analysts, scientists, architects, business stakeholders, application owners) on analytics product development and data requirements.
Provide guidance and leadership for end-to-end testing, system integration testing, and validation to support the accuracy of data transformations and data verifications used.
Build and maintain documentation, such as version-controlled work instructions, detailed design documents and architecture documentation.
Direct data engineering assignments, job scheduling, performance-tuning data processes, and troubleshooting data processing issues (including root cause resolution).
Set standards for data governance (quality, security, etc.) within the Azure data lake.
Lead coaching and mentoring and serve as a Subject Matter Expert (SME) on new technologies and best practices across data engineering (i.e. data modeling, database design, ETL design, job scheduling and monitoring, etc.)
Designs the strategic roadmap and forward analysis for data engineering, including proof of concepts and vendor management.
Direct feasibility studies and project estimates for proposed projects.
Analyzes trends, emerging technologies, and version updates to optimize data engineering's vendor relationships, technical solutions, and improve customer experience.
Partners across technology SMEs for process, policy, and procedure best practices and design.
Develop process improvement strategies based on pattern recognition with the business for proactive solutions.