Location: Bend, OR
As the Data Warehouse Lead Architect you will be responsible for the enterprise data platforms that serve the BI Portfolio and other downstream systems and applications. You will own the architectural design and data structures within the data warehouses, and will manage a team with data engineering, QA and administration skills to build, operate and maintain these high quality platforms. If this is the kind of position and company you’d be interested in - please send your resume to email@example.com. We value and encourage diversity in the workplace and women, minorities, and veterans are highly encouraged to apply. Thank you.
Job Type: Contract to Hire
More about this role:
This role is on the BI Portfolio team, and will coordinate with BI - Analytics Product DevOps, Master Data Management and Integration teams to develop efficient integrated architectures and manage dependencies.
The Data Warehouse Lead Architect sets the standards and develops the processes and procedures for staging accurate, timely, high quality data critical to the reporting, business intelligence, and analytics functions, and for publishing data to downstream systems and applications. This individual will be an expert in efficient cloud-based data architecture and how to craft robust, practical data solutions.
Primary Responsibilities and Functions:
Design, build and maintain data warehouses and their integrative architectures to support a variety of data delivery, reporting, business intelligence, analytics and end-to-end business solutions and use cases.
-Collaborate with data analysts, business stakeholders, and analytics practitioners to understand their requirements for staged data.
-Collaborate with project teams and enterprise architects to understand requirements for staged and published enterprise data.
-Set standards for integrating and maintaining the content and quality of internal and external data sources.
-Advise data engineers and lead the design of data models for relational and dimensional database schemas for a range of use cases from targeted reporting solutions to support of downstream applications.
-Manage the development and maintenance of physical database tables, views, and flat files for analytics research projects, reporting, and analytics applications.
-Architect data transformation, preparation, and data movement processes for a variety of scenarios from simple file-based export/import to enterprise-grade ETL workflows connecting multiple structured and unstructured endpoints.
-Manage the development and quality assurance of complex SQL scripts and queries in support of reporting and analytics applications.
-Select and implement appropriate technologies and methods to automate data preparation and data movement with standard data stores, tools, and platforms.
-Develop support methodologies for the delivery of ad hoc data sets to business analysts, data analysts, data scientists, teams developing proofs-of-concept, and other use cases.
-Manage and catalog enterprise data and enterprise data publication services.
-Work in an agile team environment to manage dependencies between solution developers and the data warehouse platforms.
-Operate the Data Warehouse Platform team as a dynamic learning organization supportive of other team
-Set standards for database administration and operational support for analytics data and application services, especially related to relational databases owned by the BI Portfolio team.
-Develop processes to monitor and troubleshoot manual and automated data preparation and data movement processes
-Collaborate with Information and Digital Services colleagues to develop and socialize standards and best practices to promote a culture of data management excellence
-Manage and continuously improve data work flows and query performance
-Create and maintain data dictionaries, data model diagrams, data mapping documents, analytics data requirements, operational procedures and related documentation for the data and analytics team
-Provide mentoring and expert advice to empower Digital Services colleagues to understand and utilize analytics data products, services and resources
-Provide mentoring and expert advice for the development of complex and high-performance SQL
Education and skills we’re looking for:
-Bachelor’s degree (BS or BA) in STEM related discipline or equivalent
-15 or more years relevant professional experience, preferably showing a progression from data engineering to data architecture, team leadership, and responsibility for data warehouse solutions
-Experience working in a collaborative team environment to deliver data services or application solutions; agile team experience a plus
-Demonstrated experience as the lead architect responsible for data warehouse solutions
-Demonstrated professional experience leading teams of data engineers, setting standards, policies, methodologies and quality assurance procedures
-Advanced proficiency in and passion for SQL; multiple vendors a plus; experience with Snowflake a plus
-Advanced proficiency developing data movement, integration, and/or ETL solutions with enterprise-grade platforms such as Boomi, Birst, SSIS, Dataiku, Alteryx, or similar
-Experience supporting, operating, and troubleshooting production data movement, integration, and/or ETL processes
-Strong understanding of logical and physical data modeling theory and practice; ability to describe the characteristics and applicable use cases for normalized vs dimensional designs
-Demonstrated experience developing and implementing analytic data models: reporting databases, data warehouses, data marts, and/or data cubes; able to create and execute DDL scripts
-Understanding and command of various data structure concepts including traditional RDB, NoSQL, and unstructured data; experience with geographic data (points, polygons, raster) a plus
-Familiarity with reporting, business intelligence, and analytics solution architectures; command of concepts and terminology; able to relate data engineering deliverables to these use cases
Familiarity with data security and privacy issues and accommodation of these issues in data warehouse design
-Demonstrated professional experience writing and maintaining data management documentation such as data dictionaries, data models, and integration data maps; experience using tools such as Erwin
-Proficiency and demonstrated professional experience working with flat file data formats including delimited files, XML, and JSON.
-Practical experience using solution delivery collaboration software such as Service Now, Jira, TFS, or similar
-Strong written, verbal, and communication skills; able to relate complex technical concepts to a business or semi-technical audience