Head of DataLake & Business Intelligence

Overview

We are seeking an experienced Head of DataLake & Business Intelligence to lead the evolution of our data platform, reporting ecosystem, and data-driven capabilities.This role sits at the intersection of data engineering, analytics, and platform architecture, ensuring that operational platform data can be efficiently harmonised into our Pragmatic Solutions Data Lake product, enabling scalable analytics, reporting, and AI-driven functionality.

The successful candidate will come from a strong technology and data engineering background, with deep expertise in data lake architectures, modern warehouse structures, and large-scale data processing.

While the core OLTP database architecture (MySQL) remains owned by the platform engineering teams, this role will act as a critical consumer and architectural partner, ensuring that operational data structures can be efficiently ingested, modelled, and transformed into reliable analytical datasets within the data platform. The role also carries responsibility for ensuring that the data platform is cost-efficient, scalable, and capable of supporting next-generation AI-enabled reporting and operational insights.

Key Responsibilities

Data Platform Ownership

• Own the architecture, evolution, and operational management of the company’s data platform, including the data lake and analytical warehouse layers.

• Lead the development and management of a modern lakehouse architecture built on Iceberg or similar table formats.

• Oversee the integration and operation of AWS data technologies including Glue, Athena, and associated data lake tooling.

• Ensure robust data ingestion, transformation, enrichment, and governance pipelines are in place.

OLTP Data Consumption & Harmonisation

• Act as the primary consumer of operational platform data, working closely with engineering teams to ingest and harmonise data from MySQL OLTP environments into the data lake.
• Maintain a strong technical understanding of MySQL data structures and schema design to enable effective integration with the analytical platform.
• Influence upstream schema evolution and event structures where necessary to ensure data can be efficiently consumed and modelled within the data platform.
• Design and maintain data models that translate operational platform data into reliable analytical and reporting datasets.

Data Engineering & Infrastructure

• Lead the development of scalable data pipelines capable of supporting large-scale operational and analytical workloads.
• Ensure efficient handling of high-volume data ingestion and transformation pipelines.
• Establish best practices for data modelling, schema evolution, and dataset governance.

Reporting & Business Intelligence

• Oversee the development of operator-facing reporting frameworks, enabling clear operational, financial, and regulatory insights.
• Drive the transition away from reporting directly on operational databases toward structured reporting services powered by the data lake / warehouse layer.
• Enable scalable reporting capabilities across multiple operators, brands, and regulatory jurisdictions.

AI-Enabled Data Capabilities

• Champion the adoption of AI-driven analytics and reporting capabilities, including:
  • natural language reporting interfaces
  • automated insight generation
  • predictive analytics
  • AI-assisted data discovery
• Identify opportunities where AI can enhance operational decision-making and platform functionality through data.

Cost Management & Platform Efficiency

• Maintain strict oversight of data infrastructure costs, including compute, storage, and processing workloads.
• Continuously optimise data pipelines and warehouse structures to ensure performance and cost efficiency at scale.
• Ensure the data platform remains economically viable for both internal use and external client consumption.

Leadership & Team Development

• Lead and develop a high-performing team of data engineers, BI specialists, and analysts.
• Establish best practices across:
  • data engineering
  • analytics development
  • reporting architecture
  • data governance
• Work closely with engineering, product, and operational teams to embed data-driven capabilities across the platform.

Required Experience

• 10+ years experience in data engineering, data platform architecture, or analytics infrastructure.
• Strong experience designing and operating modern data lake or lakehouse architectures, including Apache Iceberg or equivalent technologies.
• Hands-on experience working with AWS data services, particularly:
  • AWS Glue
  • Athena
  • S3-based data lake architectures
  • Iceberg
  • Flink
• Strong understanding of MySQL database structures and schema design, particularly in relation to data extraction, ingestion, and analytical modelling.
• Proven experience designing and operating large-scale data pipelines and warehouse environments.
• Experience delivering BI and reporting platforms used by operational teams or external clients.

Technical Skills

• Expert knowledge of SQL and analytical data modelling
• Strong experience with data lake and lakehouse architectures ( Iceberg, Athena, Glue , Redshift)
• Experience building and operating large-scale data pipelines
• Strong understanding of OLTP to analytical data transformation patterns
• Familiarity with AI-driven analytics and reporting technologies
• Strong knowledge of data governance, quality, and lineage
• General cloud (AWS preferred) infrastructure knowledge.

Leadership & Personal Attributes

• Proven ability to lead and mentor highly technical teams
• Strong architectural thinking and platform-level problem solving
• Ability to work collaboratively with engineering teams responsible for core platform databases
• Passion for building scalable, data-driven platforms
• Strong focus on efficiency, cost control, and operational sustainability