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- Austin, Texas, United States
- Austin, Texas, United States
About
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 & Essential Functions
Designs data patterns that support creation of datasets for analytics; implements calculations, cleanses data, ensures standardization of data, maps / links data from more than one source. Performs data validation and quality assurance on work of junior peers and writes automated tests. Maintains / streamlines existing data pipelines end to end. Builds / supports more complex data pipelines, application programming interfaces (APIs), data integrations, data streaming solutions, predictive model implementations (quality, velocity, etc.). Identifies more complex data from upstream sources to enable new capabilities. Engages in testing of the technical solutions to ensure data integrity and system functionality of own work and broader system, E2E. Builds large-scale batch and real-time data pipelines with big data processing frameworks. Designs, develops, and maintains large data integrations to support application engineering and system integration. Diagnoses and solves production support issues related to large data pipelines. Creates documentation and training related to technology stacks and standards within assigned team. Designs and implements monitoring capabilities based on business SLA and data quality. Uses / contributes to refinement of Digital Engineering-related tools, standards, and training. Engages / collaborates with external technical teams to ensure timely, high-quality solutions. Engages with shared services teams and vendors when necessary. Works closely with Product, Data Science, Application, and Analytics teams to develop a clear understanding of data and data infrastructure needs; assists with data-related technical issues; ensures optimal data design and efficiency. Performs full SDLC process, including planning, design, development, certification, implementation, and support. Interacts with Product, Business, Analyst stakeholders to confirm data quality, discuss requirements, and support data testing. Peer reviews other team members' code; learns / adapts from peer review of own code. Contributes to overall design, architecture, security, scalability, reliability, and performance. Mentors / provides support to junior Data Engineers. Builds more complex data models to deliver insightful analytics; ensures highest standard in data integrity. Knowledge in machine learning concepts. The responsibilities and essential functions outlined above describe the general nature and level of work assigned to this position. This is not an exhaustive list of all duties, responsibilities, and skills required. Duties and responsibilities may be modified at any time based on business needs. Employees may be required to perform other job-related tasks as requested by their supervisor, subject to reasonable accommodations. Qualifications & Key Requirements
Work Experience
of experience related to data engineering - Experience in Lean Startup - Agile development methodologies - Experience working in large scale infrastructure - large data sets - and mission critical SLAs - Knowledge/Skills/Abilities
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. Education
A related degree or comparable formal training, certification, or work experience. Physical Demands & Working Conditions
Function in a fast-paced environment with the ability to work from home and / or office. Work extended hours; sit for extended periods.
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Languages
- English
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