Data Engineering Manager- Hybrid Onsite- Des Moines, Iowa

Wellabe Services Co - Des Moines, IA

Full-time - Manager

Des Moines, IA

About the position

The Data Engineering Manager is a pivotal technical leader responsible for overseeing and managing the data engineering team at Wellabe Services Co. This role is crucial in guiding the team to make significant technical decisions that lead to the development of production-grade data products, which include data infrastructure, data pipelines, and data architecture. The manager will ensure that the highest standards of data quality and performance are maintained while developing robust technical roadmaps that align with the strategic objectives of the organization. Additionally, this position will prioritize and organize the team's workload to ensure optimal efficiency and productivity. In this role, the Data Engineering Manager will also focus on fostering career growth within the team by providing mentorship opportunities and empowering team members to thrive professionally. The manager will build and lead a team of data engineers through hiring, coaching, mentoring, and hands-on career development. They will provide deep technical guidance and support the team in driving large projects that involve complex dependencies and multiple stakeholders. The manager will oversee the development and maintenance of high-performance data infrastructure and architecture, utilizing tools such as Databricks, Azure, Azure Data Factory, and other industry-leading tools. They will collaborate in technical and architectural discussions, provide direction, research and recommend frameworks, and drive decision-making processes. Furthermore, the manager will ensure that processes such as unit testing, establishing SLAs, ensuring data quality checks, and performing code reviews are effectively implemented. Collaboration with various stakeholders is essential, as the manager will gather deep domain expertise and own the delivery of projects across multiple streams. They will also provide a low-friction path for the productization of AI/ML data science projects, demonstrating proficiency and up-to-date knowledge in languages, data platforms, cloud services, and emerging technologies in data engineering and analytics. This role may also involve performing other related duties as necessary or assigned.

Responsibilities

• Build and lead a team of data engineers through hiring, coaching, mentoring, and hands-on career development.
• Provide deep technical guidance and support the team in driving large projects within complex dependencies and multiple stakeholders.
• Oversee the development and maintenance of high-performance data infrastructure and architecture utilizing tools such as Databricks, Azure, Azure Data Factory, and other industry-leading tools.
• Collaborate in technical/architectural discussions, provide direction, research and recommend frameworks, and drive decision-making.
• Oversee the processes of unit testing, establishing SLAs, ensuring data quality checks, and performing code reviews.
• Collaborate closely with technical leads to develop long-term visions and innovative strategies for data utilization.
• Collaborate with various stakeholders, gather deep domain expertise, and own delivery of projects across multiple streams.
• Provide a low-friction path for the productization of AI/ML data science projects.
• Demonstrate proficiency and up-to-date knowledge in languages, data platforms, cloud services, and emerging technologies in data engineering and analytics.

Requirements

• Bachelor's degree in computer science, business/data analytics, management information systems, information technology or related field.
• 5+ years applied experience with data engineering technologies and processes.
• 5+ years of experience implementing data architectures, dimensional models, ETL, workload scheduling and orchestration framework.
• 3+ years of hands-on experience in managing Spark clusters such as Databricks, including managing and optimizing utilization of Databricks clusters, Autoloader, DLT Pipelines, Unity Catalog.
• Experience leading teams of technologists.
• Practical cloud native experience.
• Formal training or certification on data engineering concepts, preferred.
• Experience developing Azure Data Factory pipelines, preferred.
• Experience in modernizing legacy data systems, preferred.

Nice-to-haves

• Exposure to Power BI consumption or related tools.

Benefits

• Leadership training provided.