Sr. Principal Data Engineer - Lakehouse Architecture
Summary
Lead the design and implementation of a large-scale Lakehouse architecture using Databricks and Snowflake, building scalable data pipelines and mentoring a small team of data engineers.
At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
Tech at Lilly is seeking a highly skilled Senior Data Engineer who can implement and optimize large-scale Lakehouse solutions and drive the evolution of our modern data platform while providing technical leadership to a growing team. The ideal candidate will have hands-on experience with modern data engineering technology stack and a proven track record of leading engineering talent in fast-paced environments.
What you will be doing
Design and implement comprehensive Lakehouse architecture solutions using technologies like Databricks and Snowflake platforms
Define and carry out medallion architecture standards (Bronze / Silver / Gold) across data domains, ensuring data quality, lineage, and discoverability
Lead Unity Catalog governance design: schemas, access control policies, and data contracts
Build and maintain real-time and batch data processing systems using Apache Spark (PySpark/Scala), Kafka, and Databricks Structured Streaming, and similar technologies
Architect scalable data pipelines that handle structured, semi-structured, and unstructured data to deliver AI ready data.
Develop data transformation workflows using tools like DBT, Airflow, or Databricks
Implement data governance frameworks, including data quality monitoring, lineage tracking, data time travel and security protocols.
Build data pipeline testing frameworks: unit tests, data quality assertions (Great Expectations / dbt tests), and schema validation
Define and publish data SLAs/SLOs in collaboration with data product owners; own incident response and root-cause analysis for pipeline failures
Drive adoption of modern data engineering standard processes including Infrastructure as Code, CI/CD, and automated testing
Collaborate with data scientists, analysts, and business collaborators to translate requirements into robust technical solutions
Mentor a team of 3-5 data engineers
Foster a collaborative team culture focused on continuous learning and innovation
How You Will Succeed
Proven ability to mentor junior engineers and facilitate knowledge sharing
Strong project management skills with experience leading multi-functional initiatives
Coordinate multi-functional projects and ensure effective communication between technical and business teams
Demonstrated ability to make architectural decisions and drive technical consensus
Embrace a growth mindset and actively seek opportunities to expand your leadership capabilities and technical mastery
What You Should Bring
Knowledge in the pharmaceutical or life sciences domain
Experience with streaming data technologies (Kafka,Databricks Structured Streaming)
Familiarity with data cataloging tools
Familiarity with high performance data service framework (Arrow Flight)
Expert-level proficiency in Python and SQL for data transformation and pipeline development
Strong experience with Apache Spark (PySpark or Scala) for big data processing and analytics
Hands-on experience with cloud platforms (AWS or Azure) and their data services, including S3, Glue, Redshift, IAM, and CloudWatch
Proficiency with Infrastructure as Code tools (CloudFormation)
Experience with containerization (Docker, Kubernetes) and orchestration platforms
Knowledge of data modeling techniques for both analytical and operational workloads
Hands-on expertise with Databricks: clusters, Delta Lake, Unity Catalog, Workflows, and MLflow integration
Understanding of data governance, security, and compliance requirements including GxP, HIPAA, or GDPR data frameworks in regulated industries
Experience orchestrating pipelines with Apache Airflow
Strong command of dbt for modular, tested, and version-controlled transformations
Familiarity with data quality testing frameworks such as Great Expectations or dbt tests for schema validation
Experience with data observability: freshness, volume, schema drift, and anomaly detection (Databricks Lakehouse Monitoring or equivalent)
Familiarity with open table format interoperability: Delta Sharing or Apache Iceberg
Knowledge of DataOps practices and data mesh / data product principles
Exposure to ML platform integration: MLflow experiment tracking, feature stores, or model serving
Your Basic Qualifications
Master’s degree in computer science, Engineering, or related technical field
3+ years of hands-on experience with Lakehouse architectures (Databricks, Snowflake, or similar)
7+ years of overall data engineering experience with large-scale distributed systems, including at least 3 years in a senior or lead capacity
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form () for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$132,000 - $244,200Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
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