Director - Data Engineering

Job Description

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

Job Description

We are seeking a strategic Director of Data & AI Engineering to lead the growth and evolution of our data engineering function. This role will play a pivotal part in designing scalable platforms, enabling advanced AI and ML applications, and building a world-class engineering team. The ideal candidate is both a seasoned technical leader and a visionary strategist who thrives at the intersection of innovation, execution, and impact. You will collaborate with internal and client teams to develop systems and infrastructure that power intelligent products and data-driven decision-making. You will also build and mentor a high-performing team of Data and AI Engineers, foster a modern data culture, and champion best practices for scalable architecture, AI integration, and engineering excellence.

Responsibilities

Solution Design & Engineering Leadership

- Architect and build scalable, high-performance data and AI pipelines using tools such as Spark, PySpark, SQL, Python, DBT, Airflow, and cloud-native platforms (AWS, GCP, or Azure).
- Lead the design of hybrid/on-prem data platforms, incorporating security, governance, and performance optimization.

Strategic Client & Stakeholder Engagement

- Serve as a trusted technical advisor to internal and external stakeholders.
- Translate complex business needs into practical engineering solutions and oversee the end-to-end delivery lifecycle.

AI-Driven Productivity & Innovation

- Introduce and scale AI-driven tools and practices to accelerate development and enhance data quality, resilience, and maintainability.
- Champion the adoption of generative AI and foundation models to enable intelligent automation and insight generation.

Growth & Team Leadership

- Build, lead, and inspire a diverse team of Data Engineers, ML Engineers, and AI Specialists.
- Set a clear vision and goals, provide mentorship, and cultivate a strong engineering culture and standards.

Platform and Data Strategy

- Lead initiatives to modernize data infrastructure, improve data discoverability, and support real-time analytics and experimentation.
- Collaborate cross-functionally to shape product data strategies and influence the overall AI roadmap.

Presales & Business Development Support

- Partner with sales and solution teams to craft compelling proposals, technical solutions, and client presentations.
- Represent the engineering function in client discussions, workshops, and RFP responses to articulate value and differentiation.
- Support opportunity scoping, estimation, and roadmap planning for prospective engagements.

Qualifications

- 10+ years of experience in data engineering, AI/ML engineering, or product/platform engineering.
- Proven track record of leading high-performing teams and managing senior engineers and managers.
- Bachelor's or master's degree in computer science, Engineering, or a related field.
- Extensive experience with big data technologies and modern cloud ecosystems.
- Strong knowledge of AI/ML methods and their real-world applications.
- Experience in social media, content platforms, or high-scale product companies (e.g., Meta, LinkedIn, Google).
- 5+ years managing large teams (20+ engineers and managers).
- Demonstrated success in growing a data platform from 01 or scaling through significant growth phases.
- Exposure to Generative AI, LLMs, embeddings, recommender systems, or real-time personalization.
- Experience supporting presales, technical solutioning, and client-facing engineering roles.

Additional Information

- Strategic vision with hands-on technical expertise
- Excellent communication and stakeholder engagement skills
- Strong leadership, talent development, and recruitment capabilities
- Passion for solving complex, ambiguous problems with AI and data
- Deep understanding of large-scale distributed systems, data modelling, and ML pipeline orchestration