This page contains product affiliate links.
The position of Data Engineer in Analytics, specifically focusing on technical leadership, involves significant responsibilities aimed at driving forward Meta's analytical capabilities. One of the key tasks involves proactively steering the vision for data foundations and analytics to accelerate the creation and improvement of cross-platform components, notably within Instagram. This vision is not only about strategic planning but also about the tactical execution necessary to reach set goals.
As part of the role, the Data Engineer is expected to conceptualize and oversee the data architecture for various large-scale projects. This involves evaluating the design along with operational cost-benefit tradeoffs within systems, ensuring that the most efficient and effective solutions are deployed. The position also requires crafting and contributing to frameworks that enhance the efficiency and effectiveness of logging data. This means working closely with data infrastructure to quickly address and resolve any emerging issues.
Building strong, cross-functional relationships is another critical aspect of the job. The Data Engineer will collaborate with Data Scientists, Product Managers, and Software Engineers to deeply understand their data needs and drive the delivery of solutions tailored to those needs. Additionally, the role involves defining and managing Service Level Agreements (SLAs) for datasets within assigned areas of responsibility, ensuring high standards are maintained and data integrity is prioritized.
The Data Engineer must be adept at determining and implementing security models based on privacy requirements, ensuring that all necessary safeguards are in place and adhered to. Addressing data quality issues promptly and evolving governance processes within their areas of responsibility is also required, ensuring that the data used is both reliable and secure.
Another significant responsibility involves designing, building, and launching collections of sophisticated data models and visualizations. These are created to support various use cases across different products or domains. The role also entails solving complex data integration issues, employing optimal ETL patterns, frameworks, and query techniques, and making use of both structured and unstructured data sources.
The Data Engineer is also expected to help maintain existing processes, optimize complex code through advanced algorithmic concepts, and streamline pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts. This focus on optimization is aimed at ensuring that data processes are as efficient and effective as possible.
The minimum qualifications needed for this role include a Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience. The candidate must have over ten years of experience in the data warehouse space, custom ETL design, implementation, maintenance, object-oriented programming languages, schema design, dimensional data modeling, and SQL statement writing. Additionally, they should have experience analyzing data to identify deliverables, gaps, and inconsistencies, and in managing and communicating data warehouse plans to internal clients.
Preferred qualifications include a BS/BA in a technical field, Computer Science, or Mathematics, experience working with either a MapReduce or an MPP system, practical knowledge of Python, experience working autonomously within global teams, and experience influencing product decisions with data.
Interested candidates can apply through: Meta Careers.
This job offer was originally published on We Work Remotely
This job offer summary has been generated using automated technology. While we strive for accuracy, it may not always fully capture the nuances and details of the original job posting. We recommend reviewing the complete job listing before making any decisions or applications.
