Step into the future with Boehringer’s Enterprise Data, AI & Platforms (EDP) team!

At Boehringer Ingelheim, we believe Data & AI have the power to transform healthcare and improve the lives of millions of patients and animals. As a key member of the EDP team, you will be part of a passionate team to build a strong data & AI culture, deliver on key data transformation initiatives, and shape the future of data-driven decision making across our global organization.

We are seeking a highly skilled and experienced Data Engineer to design, build, and maintain our scalable and robust data infrastructure on a cloud platform. In this pivotal role, you will be instrumental in enhancing our data infrastructure, optimizing data flow, and ensuring data availability.. You will be responsible for both the hands-on implementation of data pipelines and the strategic design of our overall data architecture.

If this is your passion – not just a job, apply now and be part of something truly meaningful.

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.

This role is located in our Ridgefield, CT campus

Compensation Data

Duties & 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 data scientists, analysts, and other business stakeholders to understand data requirements and deliver solutions.
Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift) 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 present possible solutions or improvements.
Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices.

Requirements

Data Engineer

Associate degree in Computer Science or MIS with a minimum of 4 years experience; or Bachelor degree in Computer Science, or MIS, or related field with a minimum of 2 years of experience; or a Master degree in Computer Science, MIS, with minimum 1 year of experience; or relevant Business or IT experience of minimum of 4 years.
Moderate level of technical understanding and demonstrated knowledge in integrating data between applications and data warehouses
Knowledge of project management and experience working on project teams required.
Moderate knowledge of and experience with life cycle methodology,
Exposure to or experience in Expertise in one or more of a major cloud platform (AWS, Azure or GCP)
Moderate knowledge of and experience with the software development lifecycle.
Experience working in project teams and contributing to a successful outcome
Hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake Formation
Proficiency in Python and SQL

Sr. Data Engineer

Associate degree in Computer Science, MIS or related field with a minimum of 8 years experience; or Bachelor degree in Computer Science, or MIS, or related field with minimum of 4 years of experience; or a Master degree in Computer Science, MIS, or related field with minimum 2 years of experience; or relevant Business or IT experience of minimum of 4 years.
Cloud Expertise: Expert-level proficiency in at least one major cloud platform (AWS, Azure, or GCP) with extensive experience in their respective data services (e.g., AWS S3, Glue, Lambda, Redshift, Kinesis; Azure Data Lake, Data Factory, Synapse, Event Hubs; GCP BigQuery, Dataflow, Pub/Sub, Cloud Storage); experience with AWS data cloud platform preferred
SQL Mastery: Advanced SQL writing and optimization skills.
Data Warehousing: Deep understanding of data warehousing concepts, Kimball methodology, and various data modeling techniques (dimensional, star/snowflake schemas).
Big Data Technologies: Experience with big data processing frameworks (e.g., Spark, Hadoop, Flink) is a plus.
Database Systems: Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).
DevOps/CI/CD: Familiarity with DevOps principles and CI/CD pipelines for data solutions.
Hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake Formation
Proficiency in Python and SQL

Desired Skills, Experience and Abilities

4+ years of progressive experience in data engineering, with a significant portion dedicated to cloud-based data platforms.
ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data Factory, AWS Glue, dbt).
Data Governance: Understanding of data governance, data quality, and metadata management principles.
AWS Experience: Ability to evaluate AWS cloud applications, make architecture recommendations; AWS solutions architect certification (Associate or Professional) is a plus
Familiarity with Snowflake
Knowledge of dbt (data build tool) Strong problem-solving skills, especially in data pipeline troubleshooting and optimization

Eligibility Requirements:

Must be legally authorized to work in the United States without restriction.
Must be willing to take a drug test and post-offer physical (if required)
Must be 18 years of age or older

BI USA

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