We are looking for a savvy Data Engineer to join our growing team of claims data analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up, who wants to build and lead a team towards best practices in Data Engineering. The Data Engineer will support our existing team and analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the opportunity to design our company’s claims data architecture to support our next generation of products and data initiatives.
Responsibilities for Data Engineer
- Create and maintain optimal data pipeline architecture.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python, Azure Data Factory, Databricks and Azure Database Technologies.
- Build analytics tools using Power BI, D3 and C# that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across projects through multiple data centers and Azure regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing claims data pipelines, architectures/data models and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Experience with the Agile workflow, Test Driven Development, and continuous improvement/continuous deployment.
- Strong analytic skills related to working with structured and unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management using Azure Automation, Azure Function Apps, and Azure Data Factory.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of Azure Automation, Azure Data Factory, and highly scalable ‘big data’ data stores such as Azure Blob Storage, Azure Data Lake and Azure CosmosDB.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer or Data Modeler role, who has attained a Graduate degree in Software Engineering, Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Spark, Databricks, Parallel Data Warehouses, Cosmos DB.
- Experience with building relational SQL Data Warehouses and Claims Data Models.
- Experience with data pipeline and workflow management tools: Azure Data Factory, SSIS.
- Experience with Azure cloud services: Azure Data Warehouses, Azure Automation, Azure Function Apps.
- Experience with object-oriented/object function scripting languages: Python, C#, Scala, VBA, etc.
- Experience with systems scripting languages: Batch Scripts, Powershell.
- Experience with Git/GitHub and automating builds.
TRINITY is a trusted strategic partner, providing evidence-based solutions for the life sciences. With over 20 years of experience, we are committed to solving our clients’ most challenging problems through exceptional levels of service, powerful tools, and data-driven insights.
TRINITY’s range of products and services includes industry-leading benchmarking solutions, powered by TGaS. To learn more about how we are elevating life sciences and driving from evidence to action, visit trinitylifesciences.com.