Senior Data Engineer (Austin, or Dallas

Senior Data Engineer

As a Senior Data Engineer, you'll use an advanced analytical, data-driven approach to drive a deep understanding of our fast-changing business and answer real world questions. You'll work with stakeholders to develop a clear understanding of data and data infrastructure needs, resolve complex data-related technical issues, and ensure optimal data design and efficiency. Key responsibilities include designing data patterns that support creation of datasets for analytics, implementing calculations, cleansing data, ensuring standardization of data, mapping/linking data from more than one source, performing data validation and quality assurance, maintaining/streamlining existing data pipelines, building/supporting more complex data pipelines, application programming interfaces (APIs), data integrations, data streaming solutions, predictive model implementations, identifying more complex data from upstream sources to enable new capabilities, engaging in testing of the technical solutions to ensure data integrity and system functionality, building large-scale batch and real-time data pipelines with big data processing frameworks, designing/developing data integrations to support application engineering and system integration, designing/developing/maintaining large data pipelines, creating documentation and training related to technology stacks and standards, designing/implementing monitoring capabilities based on business SLA and data quality, using/contributing to refinement of Digital Engineering-related tools, standards, and training, engaging/collaborating with external technical teams to ensure timely, high-quality solutions, engaging with shared services teams and vendors when necessary, working closely with Product, Data Science, Application, and Analytics teams to develop a clear understanding of data and data infrastructure needs, assisting with data-related technical issues, ensuring optimal data design and efficiency, performing full SDLC process, including planning, design, development, certification, implementation, and support, interacting with Product, Business, Analyst stakeholders to confirm data quality, discuss requirements, and support data testing, peer reviewing other team members code, learning/adapting from peer review of own code, contributing to overall design, architecture, security, scalability, reliability, and performance, mentoring/providing support to junior Data Engineers, building more complex data models to deliver insightful analytics, ensuring highest standard in data integrity, and knowledge in machine learning concepts.

Qualifications and key requirements include experience related to data engineering, experience in Lean Startup and Agile development methodologies, experience working in large scale infrastructure and large data sets and mission critical SLAs, advanced knowledge of Lean Startup/Agile methods, knowledge of business intelligence, analytics and reporting, and application integration, knowledge of data architectures such as data warehouse, data lake, and data mesh and when to apply, strong working understanding of data architecture and data modelling best practices and guidelines for various data and analytic platforms, strong working understanding of coding standards and design principles/patterns, strong prioritization skills, strong verbal/written communication and data presentation skills, ability to deliver on ambiguous projects with incomplete information, ability/willingness to learn new technologies as they emerge, ability to calmly work under pressure, ability to work a flexible schedule as needed, ability to collaborate across multiple work locations, ability to work within a team, and willingness to take feedback from peers and mentors, a related degree or comparable formal training, certification, or work experience.