We are an industry leader with an immediate need for a Solutions Architecture Lead for Data Solutions. This is a direct hire, permanent role located in Fairfax, VA. Relocation assistance IS available for candidates not local to Northern Virginia. This role has a hybrid work schedule with 2 days in the office and three days work-from-home.
In this role, you will be responsible for setting high-level strategy for architecture and business applications that are data-focused. You will also aid the Lines of Business by providing critical solutions using the latest cloud technology.
- Work with business stakeholders and executive management on technologies, architecture solutions, and alignment with standards and roadmaps.
- Define architecture patterns, architecture project work, data patterns and architecture solutions.
- Advise business stakeholders and other IT teams regarding data architecture standards, best practices and company policies.
- Drive application architecture decisions, lead application integration and design discussions among multiple groups, and influence key decisions for technology and infrastructure architecture.
- Bachelors Degree and 10 years of hands on experience in solutions and data architecture in large-scale, enterprise environments.
- 12 years broad technology experience across areas such as application development, infrastructure platforms, SQL/NoSQL databases, ETL tools, rules engines, BI tools.
- 5 years experience in data analytics, data warehouse, data mart, business intelligence, big data.
- Technology experience should include several of the following: Hadoop, HBase, Hive, Oracle, Mongo, Postgres, MySQL, Informatica, Talend, Sqoop, change data capture (CDC), Microstrategy, Tableau, Snowflake.
- Current experience with cloud-based AWS technology and familiarity with the latest trends for enterprise data .
- Data architecture leadership and experience with both client server/web and cloud-based data technologies and applications.
- Knowledge of enterprise data models, taxonomies/ontologies, classifications and meta data models.