Top Data Engineer Jobs in Philadelphia, PA
Full-time Data Engineer role at SailPoint focusing on building and scaling the SailPoint Data Platform. Responsibilities include delivering efficient and reliable data engineering solutions, collaborating on designs and testing, and producing unit and end-to-end tests. Required skills include Python, SQL, communication skills, and a degree in Computer Science or a related field.
Seeking a Senior Manager, Data Engineering at Capital One Software. Responsibilities include leading a team of developers, collaborating on technical solutions, utilizing programming languages and cloud services, and providing technical and people leadership. Requires 8 years of application development experience and expertise in big data technologies and cloud computing.
Lead a team of data engineers in designing, developing, testing, and implementing technical solutions using full-stack development tools and technologies. Collaborate with Agile teams to drive a transformation within Capital One. Provide technical and people leadership to deliver cloud-based data solutions for analytical and decision support experiences.
Lead a team of developers in designing, developing, and implementing technical solutions using full-stack development tools and technologies. Collaborate with product managers and data analysts to deliver cloud-based data solutions for analytical insights. Provide technical and people leadership to drive major transformations within Capital One.
Develop ML solutions to increase safety, efficiency, and sustainability of physical operations at Samsara. Collaborate with engineering teams and partners to deliver core infrastructure and optimizations.
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Design, build, and maintain research data platforms and pipelines for analytics and data science. Collaborate with data scientists to acquire and aggregate data at scale. Develop tools to monitor platform health and performance. Collaborate on data flows for new feature prototypes. Perform data analyses and exploration as needed.
The Operations Data Analytics Senior is responsible for independently leading analytics projects to provide insights for business decisions and managing cross-functional stakeholders. This full-time seasonal role lasts 6-8 months and offers the opportunity to work on complex operational improvement projects.
The Operations Data Analytics Senior is a key role on the Operations Strategy & Excellence Team, responsible for leading complex operational improvement projects by providing insights through data analysis.
CoreWeave, a specialized cloud provider, is hiring a Data Engineer to build and maintain data infrastructure, optimize data models, develop data pipelines, and collaborate on data integration projects. Responsibilities include data security, documentation, and compliance with regulations. Qualifications include 5-10 years of experience, proficiency in programming languages, SQL skills, familiarity with cloud platforms and big data technologies, and strong problem-solving abilities. Salary ranges from $135,000 to $155,000 per year based on location and expertise.
Senior Data Consultant specializing in data conversions, responsible for designing, configuring, and testing the Origami platform to meet client needs. Responsibilities include configuring the platform, building integrations, designing data conversion mappings, and collaborating with technical resources. Required qualifications include 6+ years of software design and implementation experience, Bachelor's Degree in a related field, and proficiency in JavaScript, XML, SQL, and Visual Basic.
Atlassians have flexibility in where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Atlassian is ...
Ellevation is seeking a Data Acquisition Specialist to configure and facilitate consistent and reliable connections to data sources, work directly with partners to troubleshoot data issues, and collaborate with internal teams for data integration processes.
Build large, scalable platforms using cutting-edge data technologies. Define company data assets, own data architecture for projects, improve data quality monitoring, collaborate with cross-functional teams, design sophisticated data models.
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