• Design, build, and maintain scalable data pipelines in modern lakehouse architectures. • Develop clean, efficient, and production-ready Python and SQL code. • Implement ETL/ELT processes, transformations, and orchestration workflows. • Model data using medallion architecture (Bronze/Silver/Gold), star schemas, and SCDs. • Integrate multiple data sources (APIs, databases, SaaS platforms, flat files). • Deploy pipelines using CI/CD tools and version control best practices. • Leverage AI tools (e.g., agent-based workflows, automation scripts) to improve delivery speed and quality. • Collaborate directly with clients on requirements, architecture, and delivery updates. • Monitor, troubleshoot, and optimise pipelines for performance and reliability. • Ensure data quality, integrity, and production readiness.

Role Description We’re looking for a Senior Data Engineer to join a high-performing delivery team and work on end-to-end data solutions across modern lakehouse environments. This is a hands-on role, focused on building and shipping production pipelines—not people management. You’ll work directly with clients and senior engineers, owning delivery from ingestion through to transformation and consumption. - Design, build, and maintain scalable data pipelines in modern lakehouse architectures. - Develop clean, efficient, and production-ready Python and SQL code. - Implement ETL/ELT processes, transformations, and orchestration workflows. - Model data using medallion architecture (Bronze/Silver/Gold), star schemas, and SCDs. - Integrate multiple data sources (APIs, databases, SaaS platforms, flat files). - Deploy pipelines using CI/CD tools and version control best practices. - Leverage AI tools (e.g., agent-based workflows, automation scripts) to improve delivery speed and quality. - Collaborate directly with clients on requirements, architecture, and delivery updates. - Monitor, troubleshoot, and optimise pipelines for performance and reliability. - Ensure data quality, integrity, and production readiness. Qualifications - 5+ years of professional experience in data engineering. - Must have experience with Databricks or Fabric. - Strong Python skills for production environments. - Advanced SQL (CTEs, window functions, performance tuning, complex joins). - Hands-on experience with modern data platforms (lakehouse, pipelines, distributed processing). - Experience with dimensional modelling and analytics-ready data design. - Solid understanding of CI/CD, Git workflows, and deployment practices. - Strong communication skills with the ability to work directly with clients. - Ability to translate business requirements into technical solutions. - AI Proficiency (Required) Requirements - This role requires strong, practical experience using AI in development workflows: - Comfortable working in modern development environments with AI-assisted tooling. - Proven experience building AI-powered tools, automations, or agents with real business impact. - Ability to use AI across the development lifecycle (design, coding, debugging, testing, documentation). - Strong judgment in validating and refining AI-generated outputs. - Experience with prompt design, context handling, and tool integrations. Nice to Have - Experience with integration platforms or middleware tools. - Exposure to dbt or modern data transformation frameworks. - Experience with cloud-based data ecosystems. - Dashboarding or semantic modelling experience. - Familiarity with AI/agent frameworks or orchestration tools. - Previous consulting or client-facing project delivery. Work Arrangement & Expectations This is a remote role that will be set up as an employer of record. To ensure alignment and transparency, successful candidates will be expected to: - Disclose any existing ongoing roles or client work. - Reflect this engagement on their LinkedIn profile.

• CSAA Insurance Group is seeking a Principal Architect to serve as our Enterprise Data Architect • Supporting the design and delivery of secure, scalable data and AI platforms across the enterprise • Facilitating designs and building solutions across the enterprise • Solutions are built in a highly collaborative environment, partnering with engineering, product, and program leaders • Leads and provides direction to Application Integration, Data, and Platform architecture vision for the enterprise • Integrates a broad range of ideas regarding technical and solution architecture • Creates, guides, and partners with other architects in creating and maintaining roadmaps that connect business strategies to capabilities • Enables AI/ML use cases by supporting data pipelines, feature engineering, and model integration • Balances speed and control to support business innovation

• Identifying, creating, preparing data required for modern Data solutions and Data for AI. • Designing ETLs and ELTs for data transformations. • Designing, building and management of Datalakes architectures. • Working with Apache Hadoop projects (Spark, Hive, Pig, Oozie, Airflow, etc). • Integrating and testing Data solutions. • Creating and documenting the tests to meet requirements. • Working with Bigdata Environments. • Managing Data Cloud services, data access, security and data governance. • Analyzing and prepare data for Machine Learning workloads. • Managing monitoring and logs of applications and services.