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.
What do we need from you
- 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.
- Bachelors 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.
