Demonstrated success working with stakeholders and implementing end-to-end data solutions including data model, data pipelines and Business Intelligence products to solve complex business requirements.
Strong business acumen, critical thinking and technical abilities along with problem solving skills.
Solid experience in designing and implementing DW Architectures, OLAP technologies, Star-schema, Snowflake schema and Aggregation Techniques.
Experience in development of custom built BI and big data reporting solutions using tools like Tableau, Qlik, OBIEE, Cognos, MicroStrategy, Business Objects.
Experience architecting database management systems with traditional and big data technologies such as Oracle, SQL Server, Vertica, Cassandra, Hadoop, Spark, MongoDB. Prior experience with databases 100TB+ highly desired.
Advanced SQL and programming experience with at least one language such as Python, Scala, Java, C++ highly desired.
Experience as a technical lead or other mentorship role.
Excellent communication and presentation skills.
Bachelors or Masters in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Management or other engineering or quantitative discipline field. What we'd love to see (but isn't required):
Experience with big data solution on major cloud providers such as AWS, Azure, GCP.
Experience with structured and unstructured data.
Own and develop technical architecture, design and implementation of big data platforms and business analytics solutions data driven analytics and reporting needs.
Collaborate with your stakeholders and other business analytics team leaders to define and develop the data architecture and data solution roadmap.
Design and implement appropriate data architecture, data pipelines, reporting, dashboarding, data exploration, processes and quality controls to enable self-service Business Intelligence integration.
Act as a subject matter expert for technical guidance, solution design and best practices within the team.
Keep current on big data and data visualization technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit.
