Senior Data Engineer

Boehringer Ingelheim GmbH; Deutschland; Hybrid; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Boehringer Ingelheim GmbH is seeking a Senior Data Engineer for the Finance & Group Functions Data & Analytics team. You will help shape the future of Finance data, analytics, and AI by driving strategic data initiatives and building scalable data products on modern cloud platforms.

This role is hybrid with 2–3 days on site. You will collaborate with SAP experts, analysts, and business stakeholders to deliver trusted data foundations that enable smarter decision-making across the

Qualifikationen

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

Aufgaben

• Design, develop, and enhance scalable data products and pipelines in Finance using SAP and non-SAP data sources.
• Build transformation logic and analytics layers with dbt, including modeling, testing, and deployment best practices.
• Act as a role model for engineering excellence: version control, CI/CD, code reviews, documentation, and mentoring Data Engineers.
• Stay updated with latest industry trends to improve data engineering practices.

Kenntnisse

Data engineering

Snowflake

dbt

Python

AWS

Spark

Airflow

SAP BW

English

German language

Ausbildung

Master's degree in Computer Science or related field

Bachelor's degree with relevant experience

Tools

Iceberg

Spark

Airflow

Snowflake

dbt

SAP BW

Python

Jobbeschreibung

At Boehringer Ingelheim, we believe that Data & AI have the power to transform healthcare and improve the lives of millions of patients and animals. As a Senior Data Engineer within our Finance & Group Functions Data & Analytics team, you will help shape the future of Finance data, analytics & AI by driving strategic data initiatives, defining engineering standards, and building scalable data products on modern cloud and AI-enabled platforms.

Working closely with a passionate group of data engineers, SAP experts, analysts, data scientists and business stakeholders, you will create the trusted data foundation that powers innovation, enables smarter decision-making, and delivers measurable business value across Finance and our global organization.

This position has a hybrid setup with at least 2-3 days per week on site.

Tasks & responsibilities

• You will design, develop, and enhance scalable data products and pipelines based on SAP and non-SAP data sources and build data models in Snowflake, ensuring the availability and quality of strategically critical data assets in Finance.
• Build transformation logic and analytics layers using dbt, including modular data modeling, testing, documentation, and deployment best practices.
• Act as a role model for engineering excellence: version control, CI/CD, code reviews, documentation, and mentoring Data Engineers.
• In regard to technology evaluation you will stay updated with the latest industry trends and technologies to continuously improve data engineering practices.

Requirements

• Master’s degree in Computer Science, Engineering, or a related field and several years of professional experience as a Data Engineer, Software Developer, Data Scientist or in a similar role (or Bachelor’s degree with more relevant professional experience).
• Proven proficiency with the Apache ecosystem (Iceberg, Spark, Airflow).
• Strong experience with AWS cloud services (Glue, Lambda, StepFunctions) and Python scripting language.
• Solid hands-on experience with Snowflake and dbt including data modeling, performance tuning, and secure data access patterns.
• Experience with SAP's modern cloud data landscape and/or SAP BW data modelling is considered a strong advantage.
• Familiarity with end-to-end Finance processes (e.g. SAP FI/CO), including period-end closing, financial reporting and planning & consolidation processes.
• Demonstrated ability to work independently, manage priorities, and proactively drive work forward together with our stakeholders in a dynamic environment.
• Excellent communication skills in English (German is a strong plus), enabling clear interaction with technical and non technical stakeholders.