Remote Type: Fully Remote
Position Type Full Time
Education Level: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field; Master’s degree preferred.
Travel Percentage: 0%
Job Shift: Day
Job Category: EdTech
Director of Data Engineering and Analytics
About Us
Mission: ISM is dedicated to the advancement of school management. We provide creative strategies by combining extensive research, proven management techniques, and personalized service.
Independent School Management (ISM) is a forward-thinking organization dedicated to leveraging data to drive business insights and create innovative products. We recently built a state-of-the-art data lakehouse using Databricks and are now seeking a dynamic and experienced Director of Data Engineering and Analytics to lead our team in building and maintaining our data infrastructure, developing data assets, and establishing a robust analytics practice.
Core Purpose: Advancing School Leadership—Enriching the Student Experience
Key Responsibilities:
Thought Leadership & Vision:
- Drive and effectively communicate the data management vision and plans, collaborating closely with the CIO/CTO.
- Collaborate with operational teams and C-level leaders in Marketing, Sales, Customer Support, Product, and Finance to build data capacity and maturity.
- Champion a comprehensive data management strategy, promoting data literacy and engineering excellence.
- Proactively provide analytics and insights to leaders that support their objectives.
Product Management:
- End-to-end ownership of the data engineering and business intelligence teams, including roadmap planning, prioritization, and promoting best practices.
- Develop and deploy operational and reporting solutions to help ISM grow and deepen engagement with internal stakeholders and customers.
- Act as a key strategic partner to identify and act on opportunities to deploy data analysis and reporting products that leverage our operational and customer data innovatively.
Mentor & Build Team:
- Mentor and develop a team of data engineers and data analysts, fostering a collaborative and innovative environment.
- Ensure the data engineering and analytics team members understand the vision and objectives of the organization and how their backlog and priorities support those objectives.
- Stay abreast of analytics, data analytics, and machine learning technology trends and industry best practices to hone and maintain talent.
- Encourage the team to take advantage of self-directed learning opportunities and be comfortable dealing with ambiguity.
- Delegate tasks and responsibilities to team members and hold them accountable for completing assignments by the deadline.
Working Manager (Hands-on Role):
- Lead cross-functional analytics projects working with senior business leaders on major initiatives.
- Manage project schedules, task details, and utilize project management tools effectively.
- Drive the development of data products, including pilots and proof of concepts, and execute data strategies.
- Demonstrate a bold commitment to the total alignment of actions, words, and professional beliefs, setting the “tone at the top.”
- Leverage your strategic planning and technical knowledge of data engineering tools and data architecture definition to improve the effectiveness of data pipelines.
- Work closely with data analysts to create and present data visualizations and communicate business insights and project goals.
- Assist in data science projects.
Refine & Operationalize Processes:
- Develop supporting budget and resource plans.
- Develop and implement tools, reporting improvements, and automation to create innovative and insightful reports.
- Implement best practices for data extraction, collection, transformation, and processing.
- Establish and enforce BI standards and architecture aligning with enterprise architecture.
- Advocate for technical investment features to maintain and run existing data assets and solutions in conjunction with developing new capabilities by articulating objective risks and impacts to business value.
- Ensure compliance with all relevant data privacy regulations.
- Continuously maintain and improve the data quality bar throughout the data lifecycle, addressing data governance and third-party data challenges.
- Establish data analytics best practices.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field; Master’s degree preferred.
- 10+ years of experience in Data Engineering and Analytics, including 5+ years of successful team management experience.
- Experience in setting up data organizations and leading development teams through re-platform or modernization efforts and working towards taking the team to a steady state.
- Experience with CICD data architectures, pipeline quality, and code management.
- Experience in data science, including predictive modeling.
- Experience with SQL and NoSQL databases.
- Experience with common data languages (e.g., Python, RUST, Scala) and data warehouses (e.g., Databricks). Extensive experience with big data architectures, data modeling, and data lake principles.
- Strong understanding of data governance principles and best practices.
- Experience with Agile methodologies and project management tools.
- Strong process orientation with effective organizational communication and presentation skills.
- Proficient in analytics and reporting with 5+ years of experience translating complex data into actionable business insights.
- Accomplished partner with business leaders, technology leaders, and senior executives, able to communicate concisely and clearly to audiences of varying technical levels.
To be successful, the ideal candidate:
- Operates with autonomy.
- Has a “bar-raiser” mentality, driven to motivate and lead technical talent and to provide direct candid feedback to employees.
- Thrives on the freedom and responsibility of working in a growth-minded business that trusts their employees.
- Takes ownership of features from start to finish and collaborates well with engineers and other cross-functional roles.
- Teaches, coaches, and mentors, being a force multiplier for the team.
- Familiar with our tools, including experience with SQL, Databricks, Python, JIRA, Salesforce, FiveTran, AWS, Tableau, and more.
