Senior Analytics Engineer (Data & Agentic Analytics)

Job description

As a Senior Analytics Engineer , you will play a key role in shaping our data foundations and enabling data-driven decision-making across the organization. You will be at the forefront of our data and AI transformation , building agentic analytics solutions from the ground up and driving their adoption across business functions. You will design, develop, and maintain core data models, data marts, semantic models, and knowledge layers that use by our data users and power AI Agents across Product, Marketing, Logistics, Commercial, Finance, and beyond.

You will also champion data quality, governance, observability, and best practices to ensure our data foundations and Agentic solutions are reliable, trustworthy, and scalable. We’re looking for a curious, hands-on builder who thrives on tackling complex challenges and turning ideas into reality. You combine deep technical expertise with a product mindset, constantly exploring how emerging technologies can unlock new possibilities.

You don’t just build data pipelines and models; you reimagine how people interact with data, turning complex business questions into intuitive, AI-powered experiences. Working closely with analytics teams and business stakeholders, you will have the opportunity to shape how the entire organization makes decisions, bringing innovative ideas from concept to production and delivering tangible business impact at scale.

Main Responsibilities

Data Modeling and Architecture: Design, build, and maintain robust and scalable data marts/models that accurately represent business needs and support complex analyses.

Data Governance and Integrity

Establish and enforce data quality standards, implement data validation checks, and ensure data lineage is clearly documented. Take ownership of data integrity issues and drive their resolution.

Metrics Definition and Governance

Collaborate with function analytics teams and business stakeholders to define key metrics and ensure their consistent calculation and usage across the organization.

Analyst & Self-serve Enablement

Develop and maintain documentation, tools, and processes that empower analysts to access and utilise data effectively. Promote self-serve analytics capabilities and increase organisational data maturity.

Agentic Analytics Enablement & Governance

Collaborate with functional analytics teams and business stakeholders to curate and maintain the semantic and knowledge layers that serve as the single source of truth for metric definitions and domain context powering all AI and agentic analytics solutions. Drive the enablement and adoption of agentic analytics tools while establishing evaluation and observability frameworks to track accuracy, cost, latency, and drift for continuous performance optimization.

Performance Optimisation

Continuously monitor and optimize data processes / pipelines and queries to ensure efficient data delivery and processing.

Collaboration

Work closely with product teams, data engineers, analysts, and business stakeholders to understand requirements, gather feedback, and deliver impactful solutions.

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related field. Around 8+ years of experience in analytics, data governance and data modeling/engineering. Advanced SQL skills and experience with optimisation and data modeling techniques (e.g., dimensional modeling, star/snowflake schema). Strong understanding of data warehousing technologies, data transformation tools and ETL/ELT processes. Familiarity with data visualization (e.g., Tableau, Looker) and/or analytics enablement tools.

Excellent communication and collaboration skills, with the ability to explain technical concepts to both technical and non-technical audiences. Project management skills, experience in driving complex, large scale automation / data transformation projects in collaboration with a broad range of stakeholders across analytics, engineering, and business. Proficiency in at least one scripting language (e.g., Python, javascript) is a plus.

Hands on experience with Agentic Analytics solution design, development and rollout (e.g., semantic layer, context layer, tracing & evaluation layer, harness) is a plus Experience working on evaluation design and working with platforms like Langfuse or Phoenix is a plus.