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Job Description
- Create and maintain optimal database architecture by managing data requirements gathering and analysis for new and existing projects.
- Assemble large, complex data sets that meet functional / non-functional business requirements, support development, and maintenance of ongoing projects.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS/Cloud ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Install/explore additional OpenSource and commercial software products as needed to develop, deploy, and support the platform.
- Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions, implementation of HIPAA compliance at database design, and at an infrastructure level.
- Work with data and analytics experts to strive for greater functionality in our data systems. Develop set processes for data mining, data modeling, and data production.
- Collaborate with members of the team (eg, data architects, the IT team, data scientists) on the project’s goals.
- Design and implement database disaster recovery requirements to ensure business continuity requirements are met.
- Provide advanced systems administration and support capability.
- Analyze system performance; suggest and implement tuning as needed.
Job Requirements
- 8+ years of experience in a Data Engineer or DBA role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
- Sound working experience of designing databases for new and existing enterprise-level applications while working closely with business, analysis and development team.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- A successful history of manipulating, processing, and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Working knowledge of Application as SaaS, cloud platform, microservice architecture, containerization, multi-tenancy, application/database design for multi-tenant applications.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with big data tools, relational SQL, and NoSQL databases, including MySQL, Postgres, Cassandra, MongoDB.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. will be a plus.
- Experience of supporting day to day operational activities for the database platform like service requests and tickets, monitoring, performance tuning, troubleshooting long-running queries, locks, deadlocks, and performance issues like CPU, I/O, Memory bottlenecks, Backup and Restore SQL jobs.
