Role Description As our Senior Data Engineer, you will design, build, and own the core business data platforms and pipelines that enable analytics, reporting, and future AI/ML workloads across HSO and business units such as Dentally. You will play a strategically important role in establishing best practice data engineering foundations and embed a scalable architecture, trusted data models, robust data quality, and secure access to our healthcare data. You will work on meaningful problems that will have a high visibility and a direct impact on enabling the company strategy, product innovation, automation, and commercial outcomes. - Design and implement a modern, cloud‑native data platform on AWS, with Redshift and dbt at its core. - Build scalable, reliable data ingestion and transformation pipelines from operational, product, and commercial systems, with best gold standard data models and metrics that support commercial, customer, operational, and product analytics use cases. - Deliver trusted datasets that power core reporting, dashboards, and self‑serve analytics across the business. - Partner across Data, Product, Engineering, Commercial, Operational and Finance teams to ensure data models align with real business value drivers. - Ensure data platforms are extensible to support more advanced use cases (e.g. streaming data, advanced analytics, future machine learning and AI workloads). - Collaborate with the Head of Data & AI to support emerging MLOps and AI data pipeline needs over time. - Work with the Head of Data and AI, to define and implement best practices for data quality, testing, monitoring, and documentation using modern frameworks (e.g. dbt tests, data contracts, SLAs). - Build secure, compliant data access patterns appropriate for healthcare and regulated environments, including data minimisation, hashing, tokenisation, and role‑based access. - Own operational excellence (reliable, performant, scalable, cost aware and observable) for data ingestion and transformation pipelines. - Act as a senior technical contributor and role model within the data function. - Support knowledge‑sharing and mentoring as the team expands. Qualifications - Proven experience building data platforms and pipelines from the ground up in a modern cloud environment (AWS, Azure, GCP, Redshift, Databricks, Snowflake, dbt, etc.). - Strong data engineering fundamentals, including data modelling, ETL/ELT design, performance optimisation, governance, and reliability. - Experience scaling data systems as usage, data volume, and organisational demand grow. - Experience working in healthcare or highly regulated environments is desirable. - Hands on experience with AWS data services. - Strong experience with cloud data warehouses, ideally Amazon Redshift and/or Snowflake, Databricks. - Production experience using dbt for data transformations, testing, and documentation. - Solid SQL expertise and proficiency in at least one general purpose programming language (e.g. Python). - Experience implementing data quality frameworks, data contracts, data access frameworks, and SLAs. - Understanding of data security, privacy, and compliance considerations. - Exposure to, or strong interest in, ML/AI data pipelines (Sagemaker, Bedrock) and MLOps concepts. - Comfortable operating in ambiguity and autonomous enough to make pragmatic decisions in a greenfield environment that align to data principles. - Can focus on delivering value fast and value enablement. - Strong stakeholder communication skills, with the ability to translate technical concepts into business impact. - A mindset focused on building pragmatic, sustainable, well governed systems rather than ad-hoc solutions and workarounds. - Is curious, comfortable with ownership, and brings a continuous learner and improvement mindset. Company Description Diversity at Henry Schein One is all about you being you. Diversity and inclusion are integral to every aspect of our business, we push boundaries fuelled by a diverse set of voices and a desire to make a difference. We are proud to be an equal-opportunity employer. All qualified candidates are considered without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, or age. We welcome everyone to our team; we foster creativity and ambition throughout our business. We’re making a difference every day and you can too. - Community - Each Person is as Important as the Next - Open Communication - Diversity & Inclusion - Caring - Corporate Citizenship - People are our Greatest Asset - Career - Ethics - Recognise Creativity & Encourage it

• Design, develop, and deploy data ingestion pipelines to populate the Quantexa platform with data from diverse internal and external sources • Configure and tune the Entity Resolution engine to create a single, trusted view of customers, organizations, and counterparties across global data landscapes • Develop and implement contextual monitoring scenarios and analytics models to detect complex, multi-stage money laundering schemes and other financial crimes • Hands-on experience with the Quantexa platform and its Entity Resolution and Network Generation capabilities • Develop and optimize data models within Quantexa to support advanced network analysis and graph-based analytics • Build and customize components within the Quantexa platform to support the end-to-end investigation workflow • Analyze the performance of detection scenarios, focusing on reducing false positives and improving the accuracy of true positive alerts

Role Description We are hiring a Data Analyst Intern (Remote) who is passionate about working with data and solving real-world problems. You will collaborate virtually with our team to analyze datasets, build dashboards, and generate actionable insights. Key Responsibilities - Collect, clean, and preprocess datasets - Perform data analysis to identify trends and patterns - Create dashboards using Excel / Power BI / Tableau - Write SQL queries for data extraction and analysis - Assist in building KPIs and performance reports - Work with cross-functional teams remotely - Present insights in a clear, data-driven format - Support automation of reports and workflows Qualifications - Strong knowledge of Excel (Pivot Tables, VLOOKUP, formulas) - Basic understanding of SQL - Knowledge of data analysis & statistics - Familiarity with Python (Pandas, NumPy) is a plus - Experience with Power BI / Tableau preferred - Good communication skills (important for remote work) - Self-discipline and ability to meet deadlines Requirements - Students or graduates from B.Tech / BCA / BSc / BBA / MBA / Statistics / Economics - Freshers with strong interest in Data Analytics can apply Benefits - Work from home flexibility - Hands-on experience with real-world datasets - Mentorship from industry professionals - Opportunity for Pre-Placement Offer (PPO) - Certificate of Internship

Role Description This is a remote position. We are looking for experienced Senior Data Engineers to join a large-scale, multi-year Data Mapping and DataOps Platform modernisation programme for a major government ministry. This strategic initiative focuses on transforming how data is managed, governed, and leveraged as a core enterprise asset. - Data Engineering: Designing, building, and optimising scalable data pipelines to enhance stability, traceability, and refresh frequency. - Data Mapping & Metadata Capture: Onboarding critical financial systems into a centralised enterprise data catalogue and supporting governance initiatives. - Work will be delivered in an Agile/Scrum model, collaborating closely with data product managers and cross-functional teams. Key Responsibilities - Design, build, optimise, and maintain scalable data pipelines. - Develop and manage ELT pipelines, orchestration, and automation using Python. - Capture and onboard metadata into enterprise data catalogues. - Perform data analysis to identify patterns, anomalies, and quality improvements. - Contribute to data product design, including data models and structures. - Design and implement data models for analytics and reporting. - Build and maintain CI/CD pipelines for automated deployment. - Develop automation scripts using Python, Bash, and PowerShell. - Develop and maintain RESTful APIs for integration and interoperability. - Implement data quality checks and validation frameworks. - Set up monitoring, alerting, and performance tracking. - Develop dashboards and reporting solutions using Microsoft Fabric & Power BI. - Collaborate with stakeholders to translate business needs into technical solutions. - Ensure compliance with data governance, privacy, and security standards. - Maintain technical documentation and communicate with both technical and business teams. Qualifications - Recent (last 48 months) hands-on production experience in: - Python (data pipelines, scripting, automation) - SQL (data transformation, modelling) - Microsoft Azure & Microsoft Fabric - ELT Pipeline Development - Git (version control & collaboration) - Metadata Management & Data Catalogue onboarding - Data Product Design - Agile/Scrum methodologies - Data Analysis & Data Quality Assessment Technical Skills Required - Cloud & Platform: Microsoft Azure, Microsoft Fabric - Data Engineering: Python, SQL, Bash, PowerShell - Pipelines & DevOps: ELT pipelines, CI/CD pipelines - Data Modelling: Schema design, Metadata management, Data product design - API Development: RESTful APIs - Analytics & Reporting: Power BI, Microsoft Fabric Reporting - Version Control: Git, GitHub - Methodology: Agile / Scrum Nice to Have - Advanced Power BI (DAX, dashboarding, modelling) - Data visualization beyond standard reporting - Experience with REST API integrations - Exposure to: - Azure Synapse Analytics - Azure Data Lake - Azure DevOps - Experience in government/public sector or regulated environments - Familiarity with data governance frameworks - Experience in financial systems modernisation programs