Data Engineering Manager

Faith Technologies•Menasha, WI

About The Position

You’ve discovered something special. A company that cares. Cares about leading the way in construction, engineering, manufacturing and renewable energy. Cares about redefining how energy is designed, applied and consumed. Cares about thoughtfully growing to meet market demands. And ─ as “one of the Healthiest 100 Workplaces in America” ─ is focused on the mind/body/soul of team members through our Culture of Care. The Data Engineering Manager delivers a range of modern technology solutions while implementing best practices for key stakeholders across Faith Technologies Incorporated (FTI). This role is instrumental in shaping our data strategy, driving impactful data-driven decisions, and ensuring the successful execution of complex infrastructure and pipeline projects. You will lead and mentor a talented team of engineers while remaining a hands-on contributor, diving into data pipelines to provide technical guidance and insights as needed. Additionally, the Data Engineering Manager collaborates with cross-functional teams to ensure data availability, reliability, and performance for analytics, reporting, and data science purposes. This role leads and contributes to large-scale project data efforts, providing critical support to business partners, project managers, and vendor resources involved in project execution. The ideal candidate would have proficiency in programming languages such as Python, PowerShell, R, or Scala, along with strong experience in SQL and relational databases like MS-SQL. It also involves proficiency in data visualization tools such as Power BI or Tableau, as well as experience working with cloud-based platforms like Azure, GCP, or Databricks and big data technologies including Hadoop, Spark, and Kafka. Additionally, familiarity with NoSQL databases such as MongoDB or CosmosDB is expected.

Requirements

Bachelor’s Degree in Computer Science, Data Engineering, Statistics, or a related quantitative field.
5+ years of direct work experience in data engineering, software development, or a related role.
Minimum of 2+ years of experience leading and managing a team of technology professionals.
Proficiency in programming languages such as Python, PowerShell, R, or Scala, along with strong experience in SQL and relational databases like MS-SQL.
Proficiency in data visualization tools such as Power BI or Tableau, as well as experience working with cloud-based platforms like Azure, GCP, or Databricks and big data technologies including Hadoop, Spark, and Kafka.
Familiarity with NoSQL databases such as MongoDB or CosmosDB is expected.
Ability to work a flexible schedule is necessary.

Nice To Haves

Master's degree is a plus.

Responsibilities

Lead, mentor, and develop a high-performing team of Data Engineers.
Provide expert guidance on analytical techniques, ETL/ELT patterns, project planning, and complex problem-solving.
Conduct regular one-on-one meetings and performance reviews to ensure team alignment and growth.
Identify and recommend professional development opportunities to keep the team current with cutting-edge technologies.
Lead the planning, execution, and delivery of data infrastructure projects that align with FTI’s business objectives.
Partner with leadership across departments (e.g., Engineering, Manufacturing, Operations) to translate their needs into technical roadmaps.
Define project scope, timelines, and key performance indicators (KPIs) while leading development efforts on medium to large projects.
Present data insights, architectural recommendations, and project status to leadership in a clear and compelling manner.
Design, develop, and maintain secure data pipelines to transfer data from various sources to a data mart or lakehouse.
Develop integrations with specific SaaS applications such as Acumatica, Workday, Salesforce, and ServiceNow.
Implement and monitor data quality checks to identify and rectify inconsistencies, ensuring accuracy and validity.
Administer and optimize databases to ensure maximum availability, performance, and security.
Diagnose and resolve data-related issues promptly to minimize system downtime.
Performs other related duties as required and assigned.