C

ConvaTec Group

Develops medical devices for chronic care

Lead Full Stack Data Engineer - Fabric

Engineering LeadershipUpdated on Nov 10
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • Strong proficiency in SQL and Python for data transformation, modelling, and performance tuning.
  • Hands-on experience with Microsoft Fabric components, including Data Factory pipelines and dataflows Gen2, Lakehouse and/or Data Warehouse, and Power BI datasets, reports, and apps.
  • Strong Power BI skills, including DAX, semantic modelling, and performance optimisation.
  • Solid understanding of data warehousing and dimensional modelling concepts.
  • Experience implementing BI security models such as row-level security.
  • Familiarity with Git-based source control and CI/CD practices for BI and analytics assets.
  • Experience working with enterprise source systems such as ERP, CRM, and finance systems.
  • Strong analytical and problem-solving skills, with the ability to translate business needs into technical solutions.
  • Clear communication skills to explain complex technical concepts to non-technical audiences.
  • Strong attention to detail, documentation, and data quality.
  • Ability to work effectively in a cross-functional, collaborative environment.
  • Comfort working in regulated or compliance-driven environments.
  • Bachelor’s or Master’s degree in a relevant field, such as Computer Science, Data Science, Information Systems, or Engineering, or equivalent practical experience.
  • Typically 5+ years of experience in a BI, analytics, or data engineering role delivering end-to-end data solutions.
  • Demonstrated experience working across the full data stack, from data ingestion and modelling to reporting and user adoption.

Responsibilities

  • Own data products across the full lifecycle, from data ingestion and transformation through semantic modelling, reporting, documentation, and user adoption.
  • Design, develop, and implement full-stack data solutions from data ingestion through user-facing reports and apps.
  • Translate ambiguous business questions into well-defined data products, including data models, semantic layers, dashboards, and supporting documentation.
  • Manage delivery from discovery and prototyping through validation and production support.
  • Ensure data accuracy, integrity, and reliability across data solutions.
  • Develop and maintain ingestion and transformation pipelines using Microsoft Fabric Data Factory pipelines, dataflows Gen2, and copy activities.
  • Land, organise, and structure data using Fabric Lakehouse and/or Data Warehouse patterns.
  • Implement layered data architectures, such as bronze, silver, and gold, to ensure modular, reusable, and testable transformations.
  • Set ETL/ELT standards and implement performance optimisation and scalable design.
  • Apply data quality checks, validation rules, and monitoring to proactively identify issues.
  • Build and govern clean, well-modelled, well-documented, feature-ready data foundations for AI and machine learning.
  • Establish CI/CD for the data platform using GitHub, including branching, automated testing, and deployment pipelines, and raise engineering discipline.
  • Design dimensional and star schemas optimised for analytics use cases, including facts, dimensions, slowly changing dimensions, and conformed dimensions.
  • Build and maintain Power BI semantic models with clear, consistent business logic using DAX measures and calculated columns.
  • Develop high-quality Power BI reports, dashboards, and apps that are intuitive, performant, and aligned to business workflows.
  • Implement navigation, drill-through, parameterised views, and row-level and object-level security as required.
  • Optimise models and reports for performance, maintainability, and scalability.
  • Perform data analysis to identify trends, patterns, and opportunities that support decision-making.
  • Collaborate with stakeholders to understand analytical needs and deliver actionable insights.
  • Support advanced analytics use cases, including predictive or statistical models, in partnership with other specialists.
  • Enable AI-assisted analytics, such as Power BI Copilot, by ensuring semantic models are well-structured, described, and governed for reliable AI querying.
  • Ensure data solutions comply with data governance policies, security standards, and regulatory requirements.
  • Contribute to and follow standards for naming, workspace structure, environments, and deployment flows in Fabric.
  • Document data products, including their purpose, data sources, refresh cadence, ownership, lineage, and known limitations.
  • Contribute to shared libraries of reusable calculations, templates, and visual standards.
  • Provide structured handovers, user support, and occasional training or knowledge-sharing sessions.
  • Work with business stakeholders to prioritise work and agree success measures for data products.
  • Collaborate with data engineering, architecture, governance, and security teams to align on standards and patterns.
  • Participate in peer reviews of SQL, Python, DAX, data models, and report designs.
  • Support continuous improvement of data delivery practices, promoting full-stack ownership and reduced hand-offs.
  • Line-manage data engineers, including setting objectives, conducting one-to-ones and performance reviews, and supporting development.

About the Company

ConvaTec Group

Develops medical devices for chronic care

Convatec Group provides medical devices and services for chronic care. It designs, manufactures, and distributes products across wound care, ostomy care, continence care, and infusion care for patients and healthcare providers in nearly 100 countries. Its products aim to prevent infection, protect the skin, and support safer, easier patient care, while helping health systems lower overall costs. A notable example is the compact catheter for women, which combines discreet use with reliable protection. The company employs about 10,000 people and operates under a commitment to ongoing, reliable care—’forever caring’—to meet evolving patient and system needs. The goal is to improve patient outcomes and reduce the total cost of care through clinically and economically beneficial medical devices and services.

Company size
5,001-10,000
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1978

Recently Posted Jobs

Explore more opportunities at ConvaTec Group

See more jobs