The Role
Lead and scale the Data & AI Engineering function: set AI-first strategy, architect cloud data platforms and ETL/ELT pipelines, design and deploy LLM-, RAG-, and agentic-based AI solutions, adopt AI-assisted development tools, enforce data governance and responsible AI, and partner with stakeholders to deliver measurable business outcomes.
Summary Generated by Built In
We are seeking a highly experienced and technically strong leader to head our Data & AI Engineering function. This role will be responsible for driving the technical vision, delivery excellence, and AI-first transformation across our data engineering and analytics teams.
The ideal candidate will bring a hands-on leadership approach, combining deep expertise in data platforms and applied AI with the ability to guide teams, architect scalable solutions, and deliver measurable business outcomes.
Role Summary:
This position requires a strategic yet hands-on leader who can operate across data engineering, analytics, and AI, and drive the organization toward becoming a truly AI-native delivery function. The role demands a balance of technical depth, leadership capability, and business acumen to deliver impactful, scalable, and future-ready solutions.
Key Responsibilities:
This position requires a strategic yet hands-on leader who can operate across data engineering, analytics, and AI, and drive the organization toward becoming a truly AI-native delivery function. The role demands a balance of technical depth, leadership capability, and business acumen to deliver impactful, scalable, and future-ready solutions.
Key Responsibilities:
- Define and implement the AI-first engineering strategy, including standards, frameworks, and best practices across all engagements
- Lead, mentor, and scale a cross-functional team of data engineers, analysts, and integration specialists
- Drive adoption of AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) as an integral part of the engineering workflow
- Design and deliver advanced AI solutions, including:
- LLM integrations ( Large Language Model)
- Prompt engineering frameworks
- Agentic workflows
- RAG-based architectures
- LLM integrations ( Large Language Model)
- Architect and oversee end-to-end data solutions, including cloud data platforms, ERP integrations, and reporting systems
- Act as the technical authority, providing hands-on guidance through solution design, code reviews, and engineering best practices
- Collaborate with internal stakeholders and clients to identify opportunities for AI-driven optimization and automation
- Establish and enforce data governance, quality standards, and responsible AI practices.Required Experience
- 10+ years of experience in data engineering, analytics, or data platform development
- Minimum 5 years of hands-on experience in applied AI/ML, including LLMs and modern AI frameworks
- Proven, day-to-day experience with AI-assisted development tools (such as Cursor, Claude Code, GitHub Copilot)
- Demonstrated success in leading technical teams within consulting or managed services environments
- Strong ability to translate technical solutions into business value for stakeholders.
Mandatory Key Skills
Core Technical Skills
- Strong proficiency in Python and SQL (including stored procedures)
- Hands-on experience with cloud data platforms (Azure, Snowflake, Databricks)
- Expertise in building and managing ETL/ELT pipelines
- Experience with business intelligence tools (Power BI, Tableau, Looker)
- Deep understanding of:
- Large Language Models (LLMs)
- Prompt engineering techniques
- RAG (Retrieval-Augmented Generation) architectures
- Agentic AI frameworks
- Large Language Models (LLMs)
- Experience designing and deploying production-grade AI solutions
- Regular usage of AI-assisted development tools in coding and delivery workflows
- Proven experience in team leadership, mentoring, and capability building
- Strong architecture and code review expertise
- Ability to communicate effectively with both technical and non-technical stakeholders
- Strong problem-solving skills with the ability to convert business requirements into scalable technical solutions
- Experience in client-facing roles and consulting environments
- Ability to articulate business impact and ROI of data and AI initiatives
Preferred Qualifications (Good to Have)
- Experience with ERP platforms (SAP, Dynamics, Plex)
- Familiarity with workflow automation tools (e.g., n8n)
- Background in leading analytics consulting firms (e.g., Tiger Analytics, Fractal, Tredence)
- Contributions to open-source AI or data engineering projects.
below are the Mandatory skill sets
- Strong programming expertise in Python and SQL (including stored procedures)
- Hands-on experience in building and managing ETL/ELT data pipelines
- Experience with cloud data platforms (Azure, Snowflake, Databricks)
- Solid understanding of data architecture and end-to-end data engineering workflows
- Proven hands-on experience with Applied AI, including:
- Large Language Models (LLMs)
- Prompt Engineering
- RAG (Retrieval-Augmented Generation) architectures
- Agentic AI / workflow frameworks
- Large Language Models (LLMs)
- Demonstrated experience in building and deploying AI solutions in production environments
- Regular, hands-on usage of AI-assisted development tools such as:
- Cursor
- Claude Code
- GitHub Copilot
- Cursor
- Experience in technical leadership, including:
- Leading/mentoring engineering teams
- Solution architecture and design
- Code reviews and technical governance
- Leading/mentoring engineering teams
- Strong understanding of data + analytics ecosystem, including BI tools (Power BI, Tableau, or Looker)
- Experience working in client-facing or consulting environments
- Ability to translate business requirements into scalable technical solutions
- Strong communication and stakeholder management skills, including explaining technical concepts to non-technical audiences
Skills Required
- 10+ years in data engineering, analytics, or data platform development
- Minimum 5 years hands-on applied AI/ML experience, including LLMs
- Proven day-to-day experience with AI-assisted development tools (Cursor, Claude Code, GitHub Copilot)
- Experience leading technical teams within consulting or managed services environments
- Proficiency in Python
- Proficiency in SQL, including stored procedures
- Hands-on experience with cloud data platforms (Azure, Snowflake, Databricks)
- Experience building and managing ETL/ELT pipelines
- Experience with business intelligence tools (Power BI, Tableau, or Looker)
- Expertise in LLM integrations, prompt engineering, RAG architectures, and agentic AI frameworks
- Experience designing and deploying production-grade AI solutions
- Technical leadership: solution architecture, code reviews, mentoring, and technical governance
- Establish and enforce data governance, quality standards, and responsible AI practices
- Ability to translate technical solutions into business value and communicate with non-technical stakeholders
- Experience working in client-facing or consulting environments
- Experience with ERP platforms (SAP, Dynamics, Plex)
- Familiarity with workflow automation tools (n8n)
- Background or leadership experience at analytics consulting firms
- Contributions to open-source AI or data engineering projects
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The Company
What We Do
Valenta is a global service provider that combines AI-powered intelligent automation with on-demand staffing to help small and mid-sized businesses eliminate manual work, cut costs, and scale operations faster. They specialize in process consulting, digital transformation, and staff augmentation, delivering these as a managed service to help businesses grow through effective staffing solutions and improved operational efficiencies.
