Data Engineer (Scala, Spark, SQL)

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 key member of the IT Enterprise Data, AI & Platforms team, you will be part of a passionate group dedicated to fostering a strong data and AI culture, delivering on key data transformation initiatives, and shaping the future of data-driven decision-making across our global organization.

We are seeking a highly skilled and experienced Data Engineer to join the IT EDP Finance & Group Functions Data & Analytics team. In this role, you will play a pivotal part in enhancing our data infrastructure, optimizing data flows, and ensuring the availability and quality of strategically critical data assets from the Finance, Procurement, HR, Sustainability and IT domains in Finance & Group Functions. You will collaborate closely with data scientists and analysts to enable a consistent and scalable data delivery architecture across multiple analytics and AI use cases.

Tasks & Responsibilities

Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.

Collaborate with data architects, modelers and IT team members to help define and evolve the overall cloud-based data architecture strategy, including data warehousing, data lakes, streaming analytics, and data governance frameworks.

Collaborate with integration engineers, analysts, and other business stakeholders to understand data requirements and deliver solutions.

Optimize and manage data storage solutions and data integrations (e.g., S3, Snowflake, dbt, Snaplogic) ensuring data quality, integrity, security, and accessibility.

Implement data quality and validation processes to ensure data accuracy and reliability.

Develop and maintain documentation for data processes, architecture, and workflows.

Monitor and troubleshoot data pipeline performance and resolve issues promptly.

Consulting and Analysis: Meet regularly with defined clients and stakeholders to understand and analyze their processes and needs. Determine requirements to proactivly present possible solutions or improvements.

Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices.

Requirements

Technical Expertise

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

Proven experience as a Data Engineer, Software Developer, or similar role.

Proven proficiency with the Apache ecosystem (Parquet, Iceberg, Spark, Kafka, Airflow).

Strong hands‑on experience with AWS data services (Kinesis, Glue, AppFlow, Lambda, S3).

Solid experience with relational SQL and NoSQL databases, preferably Snowflake and/or Databricks, and dbt (dbt Labs) for building and modeling data pipelines.

Advanced skills in scripting languages such as Python or Scala.

Strong analytical capabilities for working with unstructured datasets.

Familiarity with data pipeline and workflow orchestration tools.

Knowledge of data visualization tools (e.g., Tableau, Power BI, QuickSight).

SnapLogic experience is a plus.

AWS certifications (Cloud Practitioner, Architecture, Big Data, or Data Analytics).

Excellent project management and organizational skills.

Strong written and verbal communication abilities.

Consulting and analytical mindset: ability to engage with clients and stakeholders, understand processes and needs, define requirements, and proactively propose solutions or improvements.

High level of proactiveness and problem‑solving attitude.

We are continuously working to design the best experience for you. Here are some examples of how we will take care of you:

Flexible working conditions

Life and accident insurance

Health insurance at a competitive price

Investment in your learning and development

If you have read this far, what are you waiting for to apply? We want to know more about you!

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