Senior Database Engineer

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Requirements:

• 7+ years of experience with AWS (preferred), GCP or Azure.
• 10+ years of experience designing, building, and supporting near real-time data pipelines and analytical solutions using technologies such as Postgres, Redshift, BigQuery, Hadoop, Teradata, MS SQL Server, Talend, Informatica, Power BI, and/or SSIS.
• 10+ years of experience using object-oriented programming languages (e.g., .Net, Java, Python) for data delivery in near real-time and streaming analytics.
• 10+ years of experience documenting business requirements and translating them into relational, non-relational, and dimensional data models using Erwin.
• 10+ years of experience working in agile teams delivering data solutions.
• 10+ years of experience developing Master Data Management (MDM) solutions.
• 8+ years of experience delivering solutions on public cloud platforms, preferably Google Cloud.
• Experience writing automated unit, integration, and acceptance tests for data interfaces and data pipelines.
• Ability to quickly learn new technologies and determine their best applications.
• Exceptional interpersonal skills, including teamwork, communication, and negotiation.

Responsibilities:

• Integrate multiple databases together, including Snowflake schema, Star schema, and Network model.
• Work with multiple message buses, such as Kafka and IBM MQ to targets like Redshift, Postgres, and MongoDB.
• Discover appropriate workloads and utilize the right database for performance and functionality.
• Design and deploy databases for scale based on request types.
• Ensure database recovery with sequence and time constraints.
• Collaborate with business and technology stakeholders to define future-state business capabilities and requirements, translating them into data architectures.
• Partner with platform architects to ensure implementations follow principles, guidelines, and standards.
• Analyze current technology environments for deficiencies and recommend solutions.
• Design, implement, and maintain data services and interfaces, including real-time data pipelines using emerging technologies.
• Develop continuous integration and deployment for data pipelines with automated testing.
• Utilize workflow management platforms like Airflow.
• Mentor and motivate the team to achieve organizational goals.
• Advocate for agile practices to increase efficiency.
• Maintain consistency with development standards.