Data Architect

We are currently seeking a Data Architect who can stand up enterprise data platforms to deliver novel, decision-ready information for high-profile clients. Our ideal candidate is ready to work in a leadership capacity within our Data Engineering team, and in very close collaboration with our Data Science, Development, Design, and Data Analytics divisions, to build scalable platforms spanning any number of source systems and downstream consumers, all the while applying data architecture best practices, driving end-to-end project execution, and leading a team of Data Engineers while ensuring operational efficiencies. 

We’re looking for a Data Architect who’s excited to spearhead the delivery of elegant, technology-agnostic big data platforms, and to do so by providing exceptional leadership to a team of Data Engineers, Analysts and QA.  We're creating world class systems to make our world a better place, and these systems require world class skills. 

This is a full-time position reporting to the Director of Data Engineering.  

 Responsibilities: 

• Drive successful end-to-end project execution from post-sales engagement through project closeout. Activities that drive success include, but are not limited to, partnering with the Director of Data Engineering to optimize data engineering staff planning, facilitate stakeholder interviews to gather requirements, model the client’s current state data ecosystem, architect the future state data ecosystem based on current best practices and client requirements, oversee and participate in development activities, collaborate with other divisions to define/execute deployment strategies and system support.
• Regularly interact with division leadership, subject matter experts, end users, technology vendors, and various stakeholders to ensure stakeholder buy-in and establish highly effective and efficient operating models within complex projects.
• Provide technology-agnostic technical leadership, drive technology stack selection and ensure the project team is set up for success on any number of open source, commercial, on-premise and/or cloud-based data engineering technologies.
• Develop, implement and/or extend production-quality data warehouse systems including database schemas, targeted data marts, enterprise data warehouses, and comprehensive ELT/ETL pipelines.
• Conceptualize, design, model and deploy conceptual, logical and physical data models across a multi-tiered landscape.
• As a dedicated member of an agile development team, work closely with the entire team to create a common technical vision, assist with sprint planning, groom product backlogs, and drive and/or delegate high-quality deliverables as required.
• Manage tasks and deliverables that span the development lifecycle including requirements gathering, design documents, test scripts, high-quality code, deployment cutover plans, and maintenance documentation.
• Support business development by providing input and recommendations to the Director of Data Engineering, when needed. 

Qualifications: 

• 5+ years' experience in similar positions working in an Agile environment
• Leadership experience driving project execution across the entire development lifecycle, working in a leadership role with demonstrated attention to detail.
• Significant experience working in a start-up (or similar) environment, successfully navigating ambiguity and working with multiple technology stacks (Google, AWS, SAP, Oracle, Microsoft, open source, etc.)
• Expert understanding of data architecture and performance optimization techniques including multi-node data distribution, partitioning, indexing, in-memory data structures, parallelization techniques, explain plans and/or tracing techniques, etc.
• Expert level of proficiency with SQL and/or SQL-based scripting languages
• Demonstrated experience with ELT/ETL design, development and implementation including connections to APIs, relational databases, semi-structured (JSON) and flat files (CSV), etc.
• Experience with data lineage, data profiling and data quality capabilities in a data warehouse environment
• Detailed understanding of common data warehouse security requirements including dedicated/system users and roles, row-level security, masking and/or anonymization, SSO capabilities, etc.
• Effective time management and organizational skills

Nice-to-have: 

• Healthcare experience, especially within research-focused oncology clinics.
• Experience designing, developing, and managing Data Lakehouse environments.
• Experience designing and implementing non-relational databases including graph, time series, object store, and big data Hadoop-based platforms.
• Experience with a variety of database architectures including row stores, column stores, fully in-memory systems, etc.