Generative AI - Cloud Data Engineer

Key Skills

Amazon Athena, Amazon RDS, Amazon RedShift, Analytical and Problem solving, Ansible, Apache Airflow, Automation, AWS, AWS Aurora, AWS Glue, Data Analytics, Data Architecture, Data science techniques, Enterprise Architect, ETL/ELT technologies, ITIL, Lambda, Management, Python Programming, SPARK Programming

Job Description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the globe.

This position is responsible for providing support for ETL / ELT / File Movement of data as part of an enterprise data program. The key responsibilities will be to process and move data between different compute and storage services, as well as on-premises data sources at specified intervals. The employee will also be responsible for for the creation, scheduling, orchestration and management of data pipelines.

Competency Summary

Data engineers are responsible for ensuring the availability and quality of data needed for analysis and business transactions. This includes data integration, acquisition, cleansing, harmonization and transforming raw data into curated datasets for data science, data discovery, and BI/analytics. Responsible for developing, constructing, testing and maintaining data sets and scalable data processing systems.

Data engineers work closest with Data Architects and Data Scientists. They also work with business and IT groups beyond the data sphere, understanding the enterprise infrastructure and the many source systems.

Input is raw datasets. Output is analytics-ready, integrated/curated datasets.

Key capabilities in this role family include:

• Data Acquisition - is the process of gathering and storing data in a location and format that it can be consumed for data preparation and/or downstream business uses.
• Data Preparation - is an iterative process for exploring, integrating, cleaning, validating and transforming raw data into curated datasets
• Data Publishing - is the act of releasing data in consumable form for (re)use by others.

Note: All data engineer roles should have a foundational set of knowledge in: communication, leadership, teamwork, problem solving skills, solution / blueprint definition, business acumen, architectural processes (e.g. blueprinting, reference architecture, governance, etc.), technical standards, project delivery, and industry knowledge.

Key Objectives/Deliverables

• Gather user requirements and translate them into business solutions.
• Design, develop, test, improve, and maintain new and existing solutions for data integration, data prep, ingestion, cleansing, and transforming raw data into curated datasets for business consumption.
• Incorporate deep data management expertise into solutions, including permissions, recovery, security, and monitoring.
• Validate and qualify solutions.
• Identify, troubleshoot, debug, and resolve technical issues.
• Work with business and IT groups to understand source systems and enterprise infrastructure offerings.
• Work with data from multiple data sources to build integrated views that will drive decisions
• Consult with internal customers who own the data to develop information relationships that lead to actionable insights.
• Work in Agile Sprints with business facing project teams

Minimum Position Qualifications

• Bachelor’s Degree and 5 years’ experience in the implementation of modern data ecosystems in AWS/Cloud platforms.
• Strong experience with AWS ETL/File Movement tools ( GLUE, Athena, Lambda, Kenesis and other AWS integration stack)
• Strong experience with Agile Development, Cloud formation Template, AWS CodeBuilt, AWS Code Pipeline
• Strong experience with Two or Three AWS database technologies ( Redshift, Aurora, RDS,S3 & other AWS Data Service ) covering security, policies, access management
• Strong programming Experience with Python and Spark
• Experience with Apache Airflow,Ansible & other automation stack.
• Excellent oral and written communication skills.
• A high level of intellectual curiosity, external perspective, and innovation interest
• Strong analytical, problem solving and investigative skills
• Experience in applying quality and compliance requirements
• Experience with security models and development on large data sets

Additional Preferences

• ITIL Certification

Education Requirements:

Bachelor’s Degree or relevant degree

Eli Lilly and Company, Lilly USA, LLC and our wholly owned subsidiaries (collectively “Lilly”) are committed to help individuals with disabilities to participate in the workforce and ensure equal opportunity to compete for jobs. If you require an accommodation to submit a resume for positions at Lilly, please email Lilly Human Resources ( Lilly_Recruiting_Compliance@lists.lilly.com ) for further assistance. Please note This email address is intended for use only to request an accommodation as part of the application process. Any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.