Database Administrator

at  Flywheel Digital

ABOUT FLYWHEEL

Flywheel’s suite of digital commerce solutions accelerate growth across all major digital marketplaces for the world’s leading brands. We give clients access to near real-time performance measurement and improve sales, share, and profit. With teams across the Americas, Europe and APAC, we offer a career with real impact, endless growth opportunities and the support you need to be the best you can be.

THE INTERVIEW PROCESS:

Every role starts the same, an introductory call with someone from our Talent Acquisition team. We will be looking for company and values-fit as well as your professional experience; there may be some technical role-specific questions during this call.
Every role is different after the initial call, but you can expect to meet several people from the team 1:1 and there might be further skill assessments in the form of a Take Home Assignment/Case Study Presentation or Pair Programming/Live Coding exercise depending on the role. In your initial call, we will walk you through exactly what to expect the process to be.

• Management of Tools: Manage/Install/Upgrade database systems(RedShift, SQL Server, MySQL,PostgreSQL ) to ensure that all systems are patched, configured and running optimallyLead the technology strategies from a database perspective to align to the Flywheel technology standards
• Manage the backup and recovery procedures for all systems to protect client information
• Manage and mentor team of DBA’s on and off-shore to ensure timelines are met and quality is measured
• Oversee the data board within JIRA and provide proper estimates for ideation through execution
• Drive secure solutions that perform well and scale with the organization, with a strong point of view on how things should get done
• Drive standardization on software solutions being implemented for data storage for all ETL processing. Eliminate the redundancy in tools(ie R, Python, SSIS, Glue, Knime, Data pipeline) and bring the right solutions for the right capabilityUtilize Athena for query execution and analysis on data stored in various formats in S3, optimize data retrieval and processing
• Implement/ troubleshoot for Glue automated ETL workflows, streamlining data integration process and improving efficiency
• Familiar with how airflow works and able to Orchestrate or monitor the DAGs that are running in different environments
• Familiar with Docker and how the architecture works, to facilitate consistent deployment and scalability across different infrastructures
• Familiar with Advance features of Redshift, specially WLM, AQUA node, Unload optimization and query optimization
• Experience with DMS and how it works, to be able to configure or troubleshoot any issue.
• Experience with Advance SQL server clustering concepts like Always on replication, Replication groups, seeding data between replication, troubleshoot replication issues
• Technical Leadership/Architecture: Mentor and manage junior resources
• Tasking resources to drive completion to tasks
• Determine the right data strategy for loading data efficiently and accurately
• Determine the right place for a data source to be stored to be used optimally
• Determine where data sets should be loaded for application use or reporting use. Architect the proper data model for Application performance and reporting visualization
• Document the data model/Dictionary to enable a team of analysts
• Oversee data security and best in class data access protection procedures are in place
• Development: Identify poorly running SQL and made changes to SQL or business process to correct issuesCreate custom monitoring jobs to keep database performance statistics and project future growth
• Lead team for creation of ETL to integrate disparate data sources into S3 and then into either Mysql or into Redshift.Establish KPIS that drive proactive monitoring across all systems
• Determine an archive strategy for all data that will encompass a hot, warm, cold data strategy
• As it becomes costlier to store data in RedShift, we need to determine what data should be kept there for fast retrieval and then determine what data needs to be available at a more cost-effective option
• Troubleshoot and root cause all data delays and inaccuracies to provide proactive monitoring and automation is in place