Data Engineer

Responsibilities:

• All team members must champion and model our values of partnership, curiosity, compassion, integrity, and excellence, and must contribute to a culture of continuous learning.
• Collaborate with stakeholders, data scientists and analysts to frame problems, clean, and integrate data, and determine the best way to provision that data on demand.
• Collaborate with other developers to design technology solutions that achieve measurable results at scale.
• Collaborate with data scientists to train, develop, and operationalize learning models.
• Build, design, and develop scalable, efficient data pipeline processes to manage data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets for analysts and data scientists.
• Evaluate and recommend technology and frameworks for building cross product data assets to optimize for flexibility, long-term viability, and time to market.
• Guide, mentor, influence, and adopt a cloud-first modern data architectural direction and consistently adopt the associated standards and best practices.
• Anticipate the need for data governance and work with designated committees to ensure that data modeling and data handling procedures are compliant with applicable laws and policies across data pipeline.
• Leads root cause analysis in response to detected problems/anomalies to identify the reason for alerts and implement advanced solutions that prevent recurring points of failure.
• Applies in-depth knowledge of the business to design a data model that is appropriate for the project and translates business requirements into design specification documents to model the flow and storage of data across multiple data pipelines.
• Identifies multiple, complex data sources and builds advanced code to extract raw data from identified upstream sources using query languages, tools, or machine learning algorithms, while assuring accuracy, validity, and reliability of the data across the pipeline.
• Formulate techniques for quality data collection to ensure adequacy, accuracy, and legitimacy of data.
• Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance.
• Participate in code reviews and champion the adoption of best practices.
• Support the data environment by releasing new features, resolving issues for users, and working with other technology teams.
• Monitor and analyze information and data systems and evaluate their performance to discover ways of enhancing them (such as new technologies and upgrades).
• Data engineers perform other duties as required, to meet team sprint goals.