Data Engineer

Job Title: Data Engineer
Location: Remote (Portland, OR)
Duration: Full Time Position

General Statement of Duties:
The IS Data Engineer plays a pivotal role in operationalizing and advancing data and analytics for CareOregon s business initiatives. This involves building, managing and optimizing data pipelines and moving them effectively into production for data and analytics consumers. Consumers include business data analysts, data scientists and other roles that need curated data for data and analytics use cases. The IS Data Engineer ensures compliance with data governance and data security requirements while enabling faster data access, integrated data reuse and acceleration of time-to-solution for CareOregon s data and analytics initiatives.

Essential Position Functions

Create, maintain and optimize data pipelines as workloads move from development to production for specific use cases.
Manage data pipelines through stages, beginning with ingestion of data sources through integration to consumption for specific use cases.
Utilize innovative tools, techniques and architectures to partially or completely automate tasks in order to minimize manual processes, reduce the potential for error and improve productivity.
Assist with the renovation of data management infrastructure that supports automation in data integration and management.
Partner with other Information Systems teams, business data analysts and other data and analytics consumers to refine their data requirements for initiatives and consumption.
Train data and analytics consumers about data pipelines and preparation techniques to make it easier for them to integrate and consume the data they need for their own use cases.
Apply understanding of data and domains to address emerging data requirements.
Propose innovative data ingestion, preparation, integration and operationalization techniques to optimally address data requirements.
Promote CareOregon s available data and analytics capabilities and expertise to IS staff and department leaders.
Collaborate with and educate staff and leadership on how to leverage data and analytics capabilities to achieve business goals

Knowledge, Skills And Abilities Required
Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management
Strong ability to work with IT and business staff to integrate analytics and data science output into business processes and workflows
Strong ability to partner with data science teams to leverage data science and refine and optimize machine learning models and algorithms
Strong ability to collaborate with data governance, quality and security experts to move data pipelines into production in compliance with applicable standards and certification
In depth knowledge of commonly used database programming languages for relational databases (e.g. SQL)
In depth knowledge of commonly used cloud-based data warehouse platforms (e.g. Snowflake, Redshift, etc.)
Ability to work across multiple deployment environments including cloud, on-premises and hybrid
Ability to work with multiple operating systems and containerization platforms (e.g. Docker, Kubernetes, AWS Elastic Container Service, etc.)
Ability to develop using Microsoft Azure products (e.g. Data Factory, Functions, Databricks, Monitor, etc.)
Ability to work with large, heterogeneous datasets to build and optimize data pipelines, pipeline architectures and integrated datasets
Ability to extract business value while considering automation opportunities
Adept in the use of traditional data integration technologies including ETL/ELT, data replication/CDC and API design and access
Strong ability to work with and optimize existing ETL/ELT processes and data integration, data preparation flows and helping to move them into production
Strong ability to work with analytics tools for object-oriented/object function scripting using R, Python, Java, Scala and/or similar languages
Understanding of business intelligence solutions including working knowledge of commonly used data discovery, analytics and BI software tools for semantic layer-based data discovery (e.g. Tableau, Power BI, etc.)
Strong ability to apply Agile methodologies
Ability to apply DevOps practices and tools and DataOps principles to data pipelines to improve data flows
Knowledge of emerging data ingestion and integration technologies
Possess curiosity and desire for ongoing learning about new data initiatives and how to address them
Ability to continually learn the latest versions of development tools and software products
Excellent written and oral communication skills
Ability to successfully manage multiple tasks, concurrent high priority projects and continuous deadlines
Possess a high degree of initiative, motivation, self-discipline and good judgment
Knowledge of the basic concepts of managed care preferred
Knowledge of health insurance business entities, relationships and processes preferred

Education and/or Experience
Minimum 5 years experience in data management required in roles that included all or most of the following functions:
Utilization of data integration, modeling, optimization and data quality improvement processes
Design of data and information architecture that delivers large (multi-terabyte) enterprise data warehouse solutions integrating many heterogeneous data sources
Development utilizing tools such as Microsoft SQL Server, Snowflake and/or similar tools
Development using Microsoft Azure products such as Data Factory, Functions, Databricks, Monitor and/or similar products
Data warehouse technical development that encompasses the data management life cycle and establishes end-to-end data warehousing, data management and analytics architecture