Data Engineer – Hybrid, NCR India
ABOUT LEO BERWICK AI
www.leoberwickai.com
Who we are:
Leo Berwick AI (“LB AI”) is a high-growth technology and AI advisory firm that works with PE firms and their portfolio companies across the deal lifecycle, from technology M&A services to AI strategy & execution. We believe technology can have an outsized impact on firm performance and enterprise value.
As a growth‑stage firm, we value initiative, collaboration, and high performance. We move quickly, invest in continuous learning, and are united by a shared ambition to build something exceptional, together.
About the role:
We’re hiring a Data Engineer, focused on enabling internal AI and data capabilities. This role is tightly scoped around two priority areas: AI agent development support and structured data extraction/normalization.
You will work directly with global stakeholders to turn loosely defined workflows into practical, production-ready solutions, often starting with ambiguity and little existing architecture. In addition to supporting internal innovation initiatives, you will occasionally collaborate with client-facing teams to design and deliver data-driven solutions that enhance transaction execution and client outcomes.
Success in this role requires strong business process understanding, especially where refining the problem is as important as building the solution. The ability to communicate technical concepts to both internal stakeholders and business users will be important.
This role will begin within a shared engineering model, supporting multiple use cases across the firm, and will play a key role in shaping foundational data architecture, tooling, and standards in a currently unstructured environment.
Key Responsibilities:
- Translate loosely defined business workflows into structured data and AI-enabled solutions, often without pre-existing frameworks
- Design and build pipelines to extract, normalize, and manage 20–50+ variables from financial models and internal data sources
- Replace manual data collection processes with automated ingestion and transformation workflows
- Support AI agent development by refining instruction logic, identifying gaps, and transitioning use cases to coded solutions when needed
- Build and maintain internal tools that connect model-driven data, client deliverables, and internal platforms
- Partner with consulting and deal teams to identify opportunities where data engineering and AI solutions can improve client engagement, analysis, and delivery.
- Collaborate with internal and external stakeholders to understand business requirements and translate them into scalable technical solutions.
- Contribute to establishing practical data architecture and reusable patterns across tools such as Snowflake, Databricks, or Microsoft Fabric
- Operate as a self-directed contributor across multiple use cases, delivering independently within a shared engineering model
What we are looking for:
- ~6-10 years of hands-on experience in data engineering or backend development roles
- Experience with AI/LLM-based workflows (e.g., agents, prompt-driven systems) and understanding of when custom engineering is required
- Experience working with modern data platforms (e.g., Snowflake, Databricks, Microsoft Fabric) or equivalent ecosystems
- Strong experience building data pipelines, ingestion workflows, and working with structured and semi-structured data
- Proficiency in Python or a similar language for data processing and automation
- Ability to design and normalize complex, multi-variable datasets (experience with financial or model-driven data is a plus)
- Strong problem-solving and business process understanding, with the ability to operate effectively in ambiguous, early-stage environments
- Strong communication and stakeholder-management skills, with the ability to work effectively with both technical teams and business users in internal and client-focused environments.