Senior Data Engineer

Our client is an innovative company that is using AI and data-driven evidence to match pharma and payer customers with the appropriate information they need to make informed business decisions.

• 5+ years of commercial experience with hand-on Database Design, Modeling, and Warehousing
• 5+ years experience with a modern Data Warehousing stack including Postgres and other equivalent modern technologies
• Track record of working in Scrum / Agile software teams
• Proficient in spoken and written English
• Strong experience with SQL design and implementation best-practices (i.e. index management, constraints, and foreign key relationships, etc.)
• Good understanding of common database administration tasks and concepts such as backup & restore, recovery models, integrity checks, and replication methods
• Expertise in query tuning and performance optimization
• Experience using data modeling tools like Visio, etc
• Strong SQL abilities and experience with relational database systems
• Strong knowledge of all traditional Data Warehouse-related components (Sourcing, ETL, Data Modeling, Infrastructure, BI, Reporting) and the modern tools to support those components
• Familiarity with GIT and release engineering strategies

• Bachelor’s degree or higher in a technical field of study
• Experience with AWS-based database systems (Snowflake, Redshift, RDS/Aurora, etc…), No-SQL databases, Operational Data Sources, and Data Lakes is preferred but not required
• Familiarity with the MPP Databases (Redshift or Vertica), Hadoop ecosystem, and HQL
• Strong understanding of modern SQL Server DR & scalability features. (i.e. Always On Availability Groups, Resource Governor, etc. preferred
• Familiarity with continuous delivery and DevOps
• Flexibility and creativity in solution design – including leveraging emerging technologies
• Ability to clearly explain and justify ideas when faced with competing alternatives
• Ability to design, communicate and apply effective and  architectural design patterns across a wide range of technical problems

• Work as part of multifunctional teams to own the design and architecture of the logical entity model of the client’s suite of products
• Convert logical models into physical data models employing sound database normalization techniques
• Create physical database objects like tables and views with appropriate data types, foreign keys, constraints, and upfront design and maintenance of proper indexes
• Create and maintain easy to follow technical documentation of data models
• Serve as a go-to resource for questions related to existing and proposed logical and physical data models
• Perform SQL code reviews and ensure that new database code meets company standards for readability, reliability, and performance
• Assist with resolving the performance of poorly executing stored procedures and queries
• Support team initiatives by developing tools and identifying opportunities for process automation; assist in evaluation and selection of standard tools for the department
• Support building and deploying the infrastructure for ingesting high-volume data from various sources
• Support developing and maintaining the data-related scripting for build/test/deployment automation