LRL- AWS Senior Data Engineer

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 employees around the world 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 world.

Job Summary

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. 

Medicines Development Information and Digital Solutions (MD IDS) serves a strategic function within Lilly Research Laboratories (LRL). The MD IDS team defines and influences LRL information strategies and develops solutions to enable the realization of LRL business goals. The Information Hub is a collection of data repositories containing clinical trial operational and results data. It provides rapid access to critical information in support of medicines development decisions and patient management. The team employs an array of technologies to support business needs including data warehouses, an exchange platform, and most recently an AWS-based data lake.

The Junior Data Engineer will be responsible for end to end process like taking the requirement for the enhancement,designing and changing the code and deploying to production with the help of support team. The person in this position will  work on different enhancements or maintenance of the application

Competency Summary

Data engineers are responsible for ensuring the availability and quality of data needed for analysis and business transactions. This includes data  acquisition, integration, 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.

Minimum Position Qualifications 

• Bachelor’s Degree in Computer Science or equivalent years of experience.
• 7+  years of experience with the software development life cycle spanning project initiation, development, testing, deployment, support, and retirement.
• Proficiency with Amazon Web Services (AWS), RDBMS, and SQL.
• Experience with application of requirements management and issue management for effective IT project delivery.
• Familiarity with software quality assurance methods and techniques.

Preferred Qualifications / Certifications 

•  Strong Experience in AWS Data Services like Lambda, Glue, S3, Aurora and Pyspark
• Hands on  experience using AWS(Lambda,stepfunctions,Glue,S3, Aurora),Python/Pyspark and SQL.
• Strong Analytical and Problem solving skill.
• Demonstrated knowledge of Cloud concepts and associated technologies.
• Experience in security/quality side of the application is preferable.
• Experience in architecting and implementing data integration solutions on enterprise scale.
• Background in working in  support teams from a technical expertise perspective; i.e., finding better ways to leverage and/or implement in a particular technology and influencing the team to embrace the change.
• Broad and deep technology learning agility.
• Excellent oral and written communication skills.
• Excellent self-management skills.

Previous Pharmaceutical R&D IT experience.

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 (https://careers.lilly.com/us/en/workplace-accommodation) 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 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.

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