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Principal Data Solution Architects

About the Job

The Principal Data Solutions Architect at Expert Data Architect is responsible for technical deployments. The Principal Solutions Architect will be responsible for providing the technical expertise to make Expert Data Architect customers successful.
This person will have a broad range of skills and experience ranging from data architecture to ETL, security, performance analysis, analytics, etc. Ideal candidates will have the insight to make connections between a customer’s specific business problems and best-case solutions.  Customer-facing skills to communicate that connection and vision to a wide variety of technical and executive audiences, and the technical skills to be able to not only build demos and execute proof-of-concepts but also to provide consultative assistance on architecture and implementation.

Responsabilities

  • Be a technical expert on all aspects of the at Expert Data Architect  prescribed data stack: Snowflake, Matillion, fivetran, dbt, etc. 

  • Serve as a technical lead on our most demanding, cross-functional customer projects. 

  • Ensure the quality of architecture and design of systems.

  • Functionally decompose complex problems into simple, straight-forward solutions.

  • Lead technical and design discussions with IT executives to help enterprises speed their adoption of new technologies and practices.

  • Ensure relevant technical strategies, policies, standards and best practices are applied correctly across technology programs/projects and products.

  • A Principal Architect can work across multiple projects with varied stakeholders.  He/she sets architectural direction, builds consensus, mediates conflicts providing technical leadership and advisory services to the business. He/she anticipates needs and potential objections and helps to create an environment which solicits positive contributions from all participants: engineering teams, sales team, and delivery teams.  

  • Has excellent interpersonal communication and organizational skills that are required to operate as a leading member of global, distributed teams that deliver quality services and solutions.

  • Guides others in resolving complex issues in solution architecture and solves complex, escalated aspects of a project. 

  • Work hands-on with customers to demonstrate and communicate implementation best practices on deployed technology.

  • Maintain deep understanding of competitive and complementary technologies and vendors and how to position our prescribed data analytics stack in relation to them.

  • Providing thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure; and have the team leadership and technical skills to get their solutions into production — while helping to ensure performance, security, scalability, and robust data integration.

  • Provide guidance on how to resolve customer-specific technical challenges.

  • Support other members of the Professional Services team develop their expertise.

Who We Are Looking For

  • Experience working with customers in a post-sales technical role.

  • Experience as a technical team lead, and/or mentorship of other engineers.

  • University degree in computer science, engineering, mathematics or related fields, or equivalent experience.

  • Proven client-facing written and verbal communication skills presenting to both technical and executive audiences.

  • Understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools.

  • Strong skills in databases, data warehouses, and data processing.

  • Extensive hands-on expertise with SQL and SQL analytics.

  • Detailed solution documentation (e.g. sequence diagrams, class hierarchies, logical system views, etc.) 

  • Ability and flexibility to occasionally travel to work with customers on-site. 

    Preferred skills: 

  • Familiarity and experience with common BI and data exploration tools (e.g. Microstrategy, Business Objects, Tableau.) 

  • Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. Amazon AWS, Microsoft Azure, OpenStack, etc.) 

  • Experience implementing ETL pipelines using custom and packaged tools.

  • Experience using AWS services such as S3, Kinesis, Elastic MapReduce, Data pipeline.

  • Experience with Python.

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