Data Engineer 2

Description

The team designs, builds, supports and maintains scalable, reliable data solutions so the business can make timely decisions from data.

You will own the data pipelines, integrations and analytics tooling that support reporting across the organisation, including Snowflake and Power BI.

You will work with the Development, Cloud and Security engineering teams so that data solutions are delivered and run securely and dependably.

The role looks ahead, using AI-assisted tools to speed up delivery and raise data quality, while keeping hands-on knowledge of existing data tools to run legacy integrations.

The company works in health, and this role supports the data behind its operations.

Responsibilities

• Build and run secure, scalable data pipelines and integrations across the organisation's data estate.
• Create data models, ETL and ELT pipelines, and analytics solutions in Azure Synapse Analytics, Snowflake, Power BI and related tools.
• Own the quality, performance and day-to-day support of the data solutions you deliver, legacy integrations included.
• Use AI-assisted tools such as GitHub Copilot and Claude in a responsible way to make data engineering faster, better and more efficient.
• Work with the Development, Cloud and Security teams to design, deliver and operate data solutions securely and reliably.
• Diagnose and fix complex data problems, including quality, performance and integration failures, on both new and legacy platforms.
• Maintain legacy data integrations so service continues, and plan their modernisation where it makes sense.
• Build and maintain Power BI dashboards, reports and self-service analytics for business users.
• Talk with business stakeholders to learn their data and reporting needs and turn them into technical solutions.
• Apply a security-first approach, handling data in line with governance, privacy and compliance rules.
• Help shape data architecture, standards and good practice across the organisation.
• Estimate the time and effort that data engineering tasks and projects will take.
• Work with the Cloud and Development teams so data platforms scale well within the cloud infrastructure.
• You may be asked to take on other reasonable tasks that fit your abilities.

Requirements

• Bachelor's degree in Computer Science, Data Engineering, Information Systems or a related field, or equivalent professional experience.
• 5+ years in data engineering, data warehousing or business intelligence.
• Strong hands-on experience with Snowflake or an equivalent cloud data warehouse.
• Strong hands-on experience with Power BI, including data modelling, DAX and building reports and dashboards.
• Experience building and maintaining ETL/ELT pipelines and integrations, including on legacy systems.
• Practical use of AI-assisted tools such as GitHub Copilot and Claude to improve data engineering work.
• Strong SQL and data modelling skills, including dimensional modelling and star schemas.
• Experience with Azure, AWS or GCP and their cloud-native data services.
• Understanding of data governance, data quality and data security principles.
• Experience working cross-functionally with Development, Cloud and Security engineering teams.
• Desirable: experience with Azure Synapse Analytics.
• Preferred but not mandatory: knowledge of GxP, GCP and/or TMF (Trial Master File).
• Strong problem-solving skills and the ability to diagnose and resolve complex data issues.
• Quickly absorbs and critically assesses new information, and applies it well as data and AI tools change.
• Strong communication skills, with the ability to explain technical data concepts to non-technical stakeholders.
• Makes decisions that affect the results, deadlines and quality of assigned work, and works collaboratively across the team.
• Investigates, defines and resolves complex data issues across many technical contexts.
• Keeps your own data and AI tooling knowledge current and shares what you learn with the team.
• Understands security, privacy and ethics well, and applies them to your own work and to the organisation's operations.
• Communicates fluently orally and in writing, and presents complex data concepts to technical and non-technical audiences.
• Judges when and how to use AI-assisted data tools, and promotes responsible adoption across the team.
• Working knowledge of data tools and platforms such as Snowflake and Power BI, and the ability to support legacy integrations.
• Works well with Development, Cloud and Security teams to deliver secure, reliable data solutions.
• Keeps up with emerging data and AI tools and finds efficiency gains.
• Strong analytical and problem-solving skills with a focus on security and quality.
• Bachelor's degree in computer science, data engineering, information systems, software engineering or a related field, or equivalent experience.
• 2+ years in data engineering, covering ingestion, transformation, modelling and pipeline operations across multiple data sources, or a related field.
• Preferred: certifications in cloud fundamentals or data engineering.

Conditions

Full-time position.

Listed under an affiliated company of the employer.

Equal opportunity applies to all candidates.

Benefits

• Benefits outside the US vary by country and follow local market practice.
• Eligibility and effective dates may differ for some benefits and for team members covered by collective bargaining agreements.