Remote Director of Data Engineering

Summary

Join a dynamic team at Workleap as the Director of Data Engineering, leading data infrastructure goals, making technical decisions, and collaborating with multiple teams.

Requirements

• 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

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

Preferred Qualifications

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