Über
Location: 560 Mission Street, 13th Floor, San Francisco, CA 94105. Must live within reasonable commuting distance from HQ and able to appear in office as required. Salary: $204,214 - $209,214/year Responsibilities
Design, develop, and maintain scalable data pipelines and ETL processes to collect, transform, and store large volumes of data. Collaborate with cross-functional teams to understand data requirements, identify opportunities for data integration, and propose efficient data engineering solutions. Implement data governance and quality control measures to ensure data accuracy, consistency, and integrity throughout the data lifecycle. Optimize and tune database systems and data processing frameworks for performance and scalability. Lead the evaluation, selection, and implementation of data engineering technologies, tools, and frameworks. Mentor and provide guidance to junior data engineers, assisting in their professional development. Collaborate with data scientists and analysts to support their data needs, providing efficient access to relevant datasets. Develop and maintain data models, schemas, and documentation to facilitate data understanding and accessibility. Work closely with infrastructure and DevOps teams to ensure data systems are secure, reliable, and properly integrated with existing infrastructure. Perform data profiling, analysis, and data mining tasks to identify patterns, trends, and insights in large datasets. Collaborate with stakeholders to identify business requirements and translate them into technical data engineering solutions. Implement data warehousing and data mart solutions to support reporting and analytics needs. Stay up-to-date with emerging data engineering technologies and best practices, and proactively recommend improvements to existing systems. Troubleshoot and resolve data-related issues, ensuring minimal disruption to data pipelines and systems. Collaborate with data privacy and compliance teams to ensure adherence to data privacy regulations and industry standards. Conduct performance monitoring and capacity planning to anticipate and address future data engineering needs. Develop and maintain data governance policies, procedures, and documentation. Participate in data architecture discussions and provide input on data storage, data flow, and data integration strategies. Collaborate with stakeholders to define and implement data retention and archival strategies. Continuously monitor and optimize data engineering processes, striving for efficiency, reliability, and scalability. Domestic travel required, 10%. Must live within reasonable commuting distance from HQ and able to appear in office as required. Qualifications
Master's degree or foreign degree equivalent in Information Systems Technologies or related field and four (4) years of experience in the job offered or related role. Utilizing the cloud-native integration tool Matillion, with a focus on designing orchestration jobs and developing transformation logic for data processing. Utilize Matillion to automate the process of moving and transforming data across various cloud platforms, such as Amazon Redshift, Google BigQuery, Snowflake, and Azure Synapse. Utilize Snowflake a cloud-based data warehousing platform to design and implement a powerful, scalable, and flexible solution for data storage, processing, and analytics. Design and build enterprise data lake. Design and develop workflows for managing and governing enterprise data using TIBCO Software's EBX Master Data Management (MDM) platform. Design and implement solutions to centralize, standardize, and manage critical business data across various domains, including customers, providers, claims, and locations Utilize TIBCO Data Virtualization tool to design and build abstraction layer that makes it easier for users to query and analyze data without needing to understand the technical details of the source systems. Utilize Power BI tool to create interactive visualizations, such as charts, graphs, and maps, that make it easier to understand and interpret data. Utilize techniques from statistics, computer science, and domain expertise to extract meaningful insights and knowledge from data
Sprachkenntnisse
- English
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