• betreibst und stabilisierst ELT-Pipelines auf Basis von Snowflake, dbt und Airflow • entwickelst und pflegst wartbare Datenmodelle in dbt • integrierst heterogene Datenquellen in konsistente Datensätze • baust und verantwortest Python‑basierte Ladeprozesse • implementierst Qualitätsprüfungen und Monitoring entlang der Pipeline • entwickelst und optimierst Power-BI-Dashboards und -Reports • agierst als Sparringspartner für deinen Teamlead

Role Description This is a remote position with occasional meetings and events in London and/or Sheffield. Our client is a fast-growing international consultancy specialising in data, AI and advanced analytics for major financial institutions. They are looking for a Software Engineer specialising in Analytics & Insights to design and build enterprise analytics products. The role focuses on: - Developing high-quality datasets, dashboards, and analytical tools that help business stakeholders make better decisions using data. - Integrating AI into data analytics to cut workload and free up time for analysing data and gaining insights. Key Responsibilities: - Design and build analytics datasets and semantic layers for enterprise reporting. - Develop dashboards and analytical products used by business stakeholders. - Translate business questions into measurable metrics, dashboards, and insights. - Design reusable analytics assets such as curated datasets, metrics frameworks, and analytical models. - Implement CI/CD pipelines for analytics workflows. - Work with enterprise data platforms to deliver scalable analytics solutions. - Ensure strong data quality, governance, and lineage practices. - Use AI-assisted tools and LLMs to accelerate analytics workflows, documentation, and insight generation. Qualifications - Strong SQL and data modelling skills. - Experience building analytics datasets and semantic layers. - Hands-on dashboard development using Tableau, Power BI, Looker, ThoughtSpot, or similar tools. - Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery. - Proficiency in Python or similar scripting languages for analytics, automation, or data manipulation. - Experience implementing CI/CD pipelines using Git, automated testing, and deployment pipelines. - Understanding of enterprise data governance, lineage, and data quality practices. - Strong ability to translate business questions into metrics, dashboards, and actionable insights. Requirements - Experience designing reusable metrics frameworks or analytical models (Nice to Have). - Experience working in large enterprise data environments (Nice to Have). - Experience using LLMs or AI-assisted tools to accelerate analytics workflows (Nice to Have). - Experience building analytics products directly for business stakeholders (Nice to Have). Ideal Candidate - Analytics Engineer or BI-focused Software Engineer. - Comfortable working between data engineering and business analytics. - Able to translate complex enterprise data into clear dashboards and insights. - Strong communication skills with both technical and non-technical stakeholders. Unfortunately, our client is unable to sponsor work visas, either now or in the future.

• Design and develop stakeholder-facing analytical applications, including interactive Power BI dashboards and custom HTML/CSS/JavaScript visualizations. • Apply user experience (UX) design principles — including information architecture, responsive layout, and usability heuristics — to maximize clarity across technical and non-technical audiences. • Select and implement front-end data visualization libraries to render complex dimensional relationships as intuitive, interactive experiences. • Build and maintain reporting deliverables across Power BI semantic models, interactive HTML dashboards, and formatted Excel workbooks, translating complex dimensional relationships into stakeholder-ready visualizations. • Perform exploratory, diagnostic, and predictive analysis across structured and semi-structured datasets, applying statistical methods including descriptive, inferential, and regression analysis. • Proactively mine organizational data assets to discover new insights, identify emerging trends, and surface previously unrealized opportunities that inform strategic decision-making. • Translate business objectives into measurable KPIs and build analytical frameworks through stakeholder requirements elicitation. • Communicate findings via data storytelling, narrative-driven briefings, and self-service reporting assets. • Build and maintain Power BI semantic models including DAX measure authoring, calculated table design, and row-level security configuration. • Create and maintain technical documentation covering report specifications, visualization design standards, analytical methodologies, data source mappings, and end-user reference guides.

• Lead and grow the data modeling function within Business Data & Analytics • Own the data models and transformation layer • Mentor a high-performing team of analytics engineers • Partner closely with Finance-aligned Data Analysts • Establish data engineering best practices and modeling standards