Senior Managing Director, Data Engineer Manager
Teach For AmericaAbout the role
ROLE TITLE: Senior Managing Director, Data Engineering Manager
POSITION REPORTS TO: Nicholas Peeters, Vice President, Software Engineering
APPLICATION DEADLINE: Applications will be reviewed on a rolling basis through 11:59pm ET on February 6, 2025
LOCATION: Flexible - 100% Remote
WHAT YOU’LL DO
We are looking for a strong data team leader who can reimagine the Teach For America lines of impact data architecture and data engineering processes. This role will drive strategic initiatives, and ensure the scalability and efficiency of our data systems in service of the mission outcomes we seek. You will manage a team of data engineers, leading the design and architecture for data engineering and related data domains. You will work alongside product managers, solution architects and others in a comprehensive team that focuses on our program delivery technologies.
The ideal candidate will be passionate about leveraging technology to make meaningful change and impact. This role includes the ability to analyze requirements and architect technical solutions for complex problems. We are seeking a candidate with deep expertise with various data management tools, data design and modelling, and integration techniques. The role leads a team in creating robust, efficient, and scalable data solutions that deliver our organizational objectives.
WHAT YOU’LL BE RESPONSIBLE FOR
Plan and oversee the entire data engineering process to ensure scalability and efficiency.
Ensure that we achieve data cohesion across multiple systems, platforms, and custom applications to achieve business outcomes.
Manage a team of data engineers, providing guidance and support in technical design and code review.
Develop and implement data architecture and data management strategies.
Execute complex automation tasks within the domain, including DevOps and SecOps practices.
Create and maintain data pipelines for various integration methods (event-based, batch, API).
Oversee troubleshooting production issues and coordinate with stakeholders to resolve them.
Design and advise on data modeling and reporting best practices, maintaining documentation for current setups.
Provide development and coaching to direct reports, ensuring effective talent pipelines.
Participate in strategic planning meetings to align data engineering initiatives with organizational goals.
A WEEK IN THE LIFE
Over the course of any week, the SMD, Data Engineering Manager will spend time:
Planning and overseeing data engineering projects to ensure they align with strategic goals.
Managing and mentoring a team of data engineers, providing guidance and support in their daily tasks.
Developing and implementing data architecture and management strategies to enhance system efficiency.
Architecting & executing complex automation tasks and ensuring adherence to DevOps and SecOps practices.
Architecting data pipelines for various integration methods, including event-based, batch, and API integrations.
Troubleshooting production issues and collaborating with stakeholders to resolve them promptly.
Implementing best practices for data modeling and reporting, and maintaining up-to-date documentation.
Leading strategic planning meetings that align data engineering initiatives with broader organizational objectives.
This role requires a balance of technical expertise, strategic planning, and team leadership to drive the success of data engineering projects.
YOUR EXPERIENCE
Your areas of knowledge and expertise that matter most for this role (minimum qualifications):
Expertise in data architecture, data management tools, and techniques
Proficiency in logical and physical data modeling, star schema, and performance tuning.
Experience with Azure Data tools (ADLS, Azure Service Bus, SQLMI).
Skilled in ETL techniques.
Experience with architecting Data Warehouses and Data Marts.
Experience in event-based integration, batch integration, and API integrations.
Proficiency in one or more programming languages (SQL, Python, JavaScript, Java).
Experience with reporting and BI tools.
Experience implementing complex automation (DevOps/SecOps).
Experience writing data pipelines for various integration methods.
Experience with data migrations.
Experience creating and maintaining complex reports and dashboa
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