Data Engineer

Title: Data Engineer Location: 100% Remote – EST Time zone Duration: 12 Months Should have good experience in Azure Stack (Data Lake/Blob Storage, Power BI Services, Azure Data Factory (or equivalent), Databricks) and strong on SQL Server Looking for a Sr level person –10+ Years Responsibilities The Data Engineer II supports our business goals by designing, implementing, and maintaining data pipelines using cloud-native tools in a modern data stack. Job Roles · Work independently to solve 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. · Create connectors for data pipelines to ingest data from disparate sources into 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. QUALIFICATION REQUIREMENTS · 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 preferred. · Familiarity with modern data stack components like Snowflake, dbt, Stitch, Tableau, and Airflow · Familiarity with statistical concepts and analytic modeling (e.g., regression analyses, hypothesis testing, and ML based modeling) preferred. · Experience with software engineering best practices like version control with Git and CI/CD preferred. · Experience with US healthcare and healthcare data, as well as familiarity with HIPAA guidelines, and best practices for handling and storing PHI and PII preferred. · Experience with healthcare marketing analytics, healthcare data (claims), and common medical coding sets (ICD, HCPCs, NPIs) preferred.