**Description**
**Sr Data Engineer (LATAM)**
Syneos Health® is a leading fully integrated biopharmaceutical solutions organization built to accelerate customer success. We translate unique clinical, medical affairs and commercial insights into outcomes to address modern market realities.
Every day we perform better because of how we work together, as one team, each the best at what we do. We bring a wide range of talented experts together across a wide range of business-critical services that support our business. Every role within Corporate is vital to furthering our vision of Shortening the Distance from Lab to Life®.
Discover what our 29,000 employees, across 110 countries already know:
**WORK HERE MATTERS EVERYWHERE**
**Why Syneos Health**
- We are passionate about developing our people, through career development and progression; supportive and engaged line management; technical and therapeutic area training; peer recognition and total rewards program.
- We are committed to our Total Self culture - where you can authentically be yourself. Our Total Self culture is what unites us globally, and we are dedicated to taking care of our people.
- We are continuously building the company we all want to work for and our customers want to work with. Why? Because when we bring together diversity of thoughts, backgrounds, cultures, and perspectives - we're able to create a place where everyone feels like they belong.
**Job responsibilities**
- Work independently to solve complex open-ended questions.
- Develop and maintain end-to-end data pipelines using cloud-native solutions to extract, load, and transform data from disparate data sources to a cloud data warehouse.
- Capable of formatting and distributing custom data extracts through various means (e.g., custom SFTPs, APIs (e.g., RESTful), and other bulk data transfer mediums) and optimizing data storage options based on business requirements.
- Create models to transform raw data into analytics ready data structures.
- Competent in helping to develop/design database structure and function, schema design, and database testing protocols.
- Establish and enforce engineering best practices and standards. Contribute to engineering wiki and document work.
- Design end-to-end data pipelines using cloud-native solutions to extract, load, and transform data from disparate data sources to a data warehouse.
- Contribute to the process of defining company data assets (data models) and custom client workflows, as well as standardized data quality protocols.
- Capable of independently and collaboratively troubleshooting database issues and queries for improving data retrieval times across various systems (e.g., via SQL).
- Collaborate with both technical and non-technical stakeholders including IT, Data Science, and various team members across a diverse array of business units.
- Work closely with IT team whenever necessary to help facilitate, troubleshoot, or develop database connectivity between internal/external resources (e.g., on-premises Azure Data Lakes, Data Warehouses, and Data Hubs).
- Help implement and enforce enterprise reference architecture and ensure that data infrastructure design reflects enterprise business rules as well as data governance and security guidelines.
- Communicate and collaborate with business and technical stakeholders to gather business needs as well as functional requirements that inform product and resource design and ensure that technical implementation considerations are understood and accepted.
- Mentor and coach junior team members across the business.
**Qualifications**
**What we're looking for**
- Bachelor's degree (BS/BA) in Information Systems, Software Engineering, Computer Science, Data Engineering, or related field required. Master's degree (MS/MA) preferred.
- Experience with ETL/ELT, taking data from various data sources and formats and ingesting into a cloud-native data warehouse required.
- Experience with Azure Stack (Data Lake/Blob Storage, PowerBI Services, Azure Data Factory (or equivalent), Databrick) and production level experience with on-premises Microsoft SQL Server required.
- Experience with one of the following: Python, R, and/or Scala as well as standard analytic libraries/packages (e.g., pandas, Numpy, dplyr, data table, stringr, Slick, and/or Kafka) and related distribution frameworks required.
- Strong verbal and written communication skills required.
- Familiarity with agile and lean concepts that drive towards MVPs and iterative learning to generate the desired business and technology outcomes required.
- Experience with DataRobot, Domino Data Labs, Salesforce MC, Veeva CRM.
- Experience with US healthcare and healthcare data, as well as familiarity with HIPAA guidelines, and best practices for handling and storing PHI and PII.
- Experience with healthcare marketing analytics, healthcare data (claims), and common medical coding sets (ICD, HCPCs, NPIs).
- Familiarity with modern data stack compon
