Director of Data Engineering

What is our Innovation team?       

The Innovation team is where we push the boundaries and build new products from the ground up. It's also where we build the AI capabilities for Workleap. With a startup mindset but deeper pockets and more field experience, the Innovation team constantly faces the unknown with agility and intensity.   

What is cool about the Innovation team: 

• We prioritize actions and fast iterations
• We have many small teams with minimal hierarchy
• We work directly with Workleap co-founders and other very talented and experienced teammates.

 

So, what will your new role look like?   

As the Director of Data Engineering, you will lead the team in building scalable data pipelines, warehousing, and orchestration. You will oversee the secure processing and anonymization of data flows across multiple layers, enabling AI initiatives with high-quality data.

Your key responsibilities:

• Team Leadership: Build and lead a high-performing team of data engineers and software developers to deliver on data infrastructure goals.
• Technical Leadership: Make key architectural and technology decisions to ensure the scalability, security, and efficiency of data systems across the whole organization.
• Cross-functional Collaboration: Work closely with multiple teams (Product, AI, Engineering, etc.) to align data initiatives with broader business goals and ensure seamless integration across the company.
• Data Infrastructure: Design and implement a robust data warehousing foundation, including data pipelines, orchestration, and the tools required for scalable, secure data processing.
• Pipeline Development: Build secure, multi-step data pipelines that process, anonymize, and standardize data flows from multiple sources (8+ products), ensuring high data quality and accessibility.
• Data Integration: Oversee the ingestion of data across the company’s portfolio, consolidating it into a standardized format ready for AI initiatives and advanced analytics.
• AI Enablement: Ensure that data infrastructure supports the development of AI-powered products by delivering clean, structured data for internal teams (data scientists, analysts) and external customers.
• Continuous Improvement: Stay ahead of industry trends in data engineering and AI to continuously improve the company’s data capabilities.

Qualifications:

• Proven Expertise in data architecture, data warehousing, and building scalable data pipelines, ideally in a B2B SaaS environment.
• Hands-on Leadership experience managing and scaling data teams (5-7 people), with a balance between technical leadership and people management.
• Strong Knowledge of modern data processing tools and frameworks (e.g., Spark, Kafka, Airflow, DBT, etc.).
• Experience with Data Security and anonymization, ensuring data governance and compliance across all systems.
• Cross-functional Collaboration skills to work with a range of stakeholders and deliver integrated data solutions that support business and AI goals.
• Excellent Communication Skills for conveying complex technical ideas to both technical and non-technical stakeholders.

Nice to Have:

• Experience in Azure platforms and distributed data storage solutions.
• Familiarity with modern data analytics and AI tools and frameworks.