Are you ready to embark on this journey with us?

As a Data Engineer, you will:

• Design, build, and own scalable batch and streaming data pipelines that power analytics, BI, and AI/ML use cases

• Contribute to the development of our core data platform, gaining experience with architecture,, shared frameworks, and platform tooling

• Collaborate closely with teams cross analytics, BI, AI, ML and engineering to deliver reliable and impactful data solutions

• Build and maintain data ingestion pipelines, working with data from variety of internal and external sources

• Support improvements in data reliability and trust through data quality checks, monitoring, alerting, and observability

• Work across data integration, storage optimization, and performance tuning to support growth at scale

• Support and improve cloud infrastructure for data workloads, including compute, storage, and access control

• Monitor and troubleshoot, and resolve pipeline and platform issues using our observability and monitoring tools

• Contribute to optimizing data storage and retrieval for performance and cost efficiency

• Stay curious about emerging data engineering trends and apply modern best practices to continuously improve the platform

• Share knowledge and contribute to best practices, supporting team growth and continuous improvement across the team

You will work hands-on with technologies such as:

Fuel for your success in the role

You’re motivated by building high-quality data services and enjoy working in a fast-moving, collaborative environment. You like solving complex problems, care about reliability, and are always curious about better ways to do things.

We’re looking for someone who brings:

• A Master’s degree in Computer Science, Engineering, Data Science, or a related field.

• Solid experience working with Python for data processing and automation.

• Comfort working with Git in a collaborative development workflow

• Basic knowledge of SQL, including writing queries and performing data transformation tasks.

• An interest in working with data, including preparing, cleaning, and validating datasets.

• Strong problem-solving skills with attention to detail.

• Excellent communication and collaboration skills

• A proactive, continuous-learning mindset

• Good written and spoken skills in English

What makes this role interesting

• You’ll work on the core data platform that power analytics and decision-making across the whole Abacus Medicine Group

• Exposure to modern data stacks and real-world scale challenges

• Opportunities to influence platform architecture decisions as you grow

• Hands-on experience with automation, observability, and reliability at scale

It is an advantage if you have experience or interest in:

• Cloud environments (Azure, AWS, or GCP)

• Azure Data / Delta Lake for efficient storage and processing of big data.

• Streaming or event-driven architectures

• Data governance, lineage, and access management

• Apache Spark and Databricks

• PySpark

• Orchestration tools (Azure Data Factory, Airflow, etc)

• Data modeling and transformation concepts

• CI/CD practices.

Your future colleagues

In the Data, Analytics & AI (D&A) department, we deliver end-to-end capabilities across Data Engineering, Business Intelligence, Advanced Analytics, and AI-driven automation. We are responsible for developing and operating Abacus’ enterprise data hub, including data management, orchestration, and self-service data and BI platforms. Our work spans predictive and prescriptive analytics using OR, ML, and AI, as well as applying AI to optimize workflows and enhance personal productivity across the organization.

The department consists of over 30 colleagues with diverse profiles, including Data Scientists, Data Engineers, BI Developers, Data Analysts, GenAI Engineers, and AI Advisors.