Senior Data Engineer

Overview

/About Lumanity

Lumanity is dedicated to improving patient health by accelerating and optimizing access to medical advances. We partner with life sciences companies around the world to generate evidence to demonstrate the value of their product, translate the science and data into compelling product narratives, and enable commercial decisions that position these products for success in the market. We do this through strategic and complimentary areas of focus: Strategy Consulting & Insights, Value, Access, & Outcomes, and Medical Strategy and Communications.

Responsibilities / Position overview

As a Senior Data Engineer, you will work closely with another Senior Data Engineer to manage and optimize the company’s data infrastructure. Your primary focus will be on integrating and supporting our enterprise systems—including NetSuite and Kantata (our PSA tool)—as well as our Azure-based data platform.

You will share responsibility for maintaining our Azure SQL Data Warehouse, orchestrating ETL pipelines using Azure Data Factory, and ensuring the Finance team has access to clean, timely data for Power BI reporting.

Your role will involve working with diverse data formats (relational databases, hierarchical JSON/XML, delimited files, Excel) and leveraging programming languages such as Python, Java, and (optionally) C/C++ to build and maintain robust data integrations across multiple SaaS platforms. Ensuring data consistency, quality, and flow will be at the heart of your work.

In addition, you’ll collaborate with IT, business analysts, finance, and our managed services provider (MSP) for NetSuite to deliver scalable, compliant data solutions that empower data-driven decision-making across the business.

Azure Data Platform Management:Share responsibility for the administration and optimization of the company’s Azure SQL Data Warehouse. Develop, maintain, and monitor Azure Data Factory pipelines for data extraction, transformation, and loading (ETL) from NetSuite, Kantata, and other enterprise systems. Ensure data availability, accuracy, and performance for enterprise reporting needs.Data Pipeline Development & Optimization:Design, build, and maintain scalable and robust data pipelines to integrate data from ERP and other enterprise systems.ERP System Integration:Collaborate with ERP specialists to ensure seamless integration of data between ERP systems (Oracle NetSuite and Kantata) and other enterprise systems into centralized data models.Enable BI reporting:Work alongside our reporting team to ensure business goals and needs are met through appropriate, timely, and accurate data provision.ETL Processes:Develop and maintain ETL processes to ensure efficient data extraction, transformation, and loading into data environments.Data Modelling & Architecture:Design and implement data models that meet business requirements, focusing on efficiency, reliability, and scalability.Automation & Continuous Improvement:Automate routine data processing tasks to improve efficiency and accuracy across systems, identifying areas for optimization and improvements.Data Governance & Quality:Establish and enforce data quality standards, monitoring the accuracy and integrity of data across systems. Represent data engineering on the change advisory board. Ensure compliance with regulatory requirements specific to the life sciences industry.Collaboration:Work closely with business analysts and key stakeholders to understand data requirements and deliver solutions that support analytics, reporting, and business operations.Documentation & Best Practices:Create detailed documentation of processes, data flows, and system integrations. Promote best practices in data engineering and system integration across the organization.Support & Troubleshooting:Provide technical support for data-related issues within dataflows and enterprise systems, ensuring minimal downtime and continuity of operations.Security & Compliance:Ensure data security best practices are followed and all processes comply with applicable regulations such as GDPR, HIPAA, and other life sciences-specific regulations.

Qualifications

Bachelor’s degree in computer science, data science, engineering, or related field or equivalent college qualification or 5 years equivalent work experience. 5+ years of relevant experience working in data engineering and data warehousing. Experience with designing and implementing data models for enterprise data initiatives.  Demonstrated experience leading projects involving data warehousing, data modelling, and data analysis. Proficiecy in Programming languages such as Java, Python, and C/C++ and tools such as SQL, R, SAS, or Excel Proficiency in the design and implementation of modern data architectures and concepts leveraging Azure cloud services, real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks) Proficiency with relational database technologies and SQL programming, to include writing complex views, stored procedures, and database triggers Understanding of entity-relationship modelling, metadata systems, and data quality tools and techniques Experience with business intelligence tools and technologies such as Azure Data Factory, Power BI, and Tableau Learning and adopting new technology, especially in the ML/AI realm Collaborating and excelling in complex, cross-functional teams involving data scientists, business analysts, and other stakeholders

Benefits

We offer our employees a comprehensive benefits package that focuses on what matters to you – health and well-being, personal finances, professional development, and a healthy work/life balance:

Competitive salary plus annual bonus scheme Private health insurance plus enhanced dental and optical cover Generous pension scheme Generous amount of paid days holiday Enhanced maternity and paternity pay for employees with 2+ years of service Access to comprehensive Mortgage Advisor Service Group income protection Life assurance coverage at 4x base salary EV car scheme and more

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