We are looking to hire a Data Engineer to join our Operations Analytics team. You will take responsibility for performing hands-on work required to convert existing data across various enterprise systems into a single data platform that is a collection of robust, analytics, and reporting ready datasets. This includes learning and understanding of upstream processes, pipelines, and source systems. The role will work in conjunction with analytics teammates to lay the data-foundations for analytic tool development, understand the business context of data assets, and actively maintain and improve the team’s portfolio of value-add logic/code and data processes. Additionally, the role will work with various functional units to ensure solutions are successfully deployed, operationalized, and maintained.
• Design Extract-Transform-Load (ETL) Workflows for data migration from various sources to data warehouse using batch or incremental loading strategies.
• Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed.
• Excellent understanding of development processes and agile methodologies
• Document database design including data modeling, metadata and business process flow for the new business integration requirements.
• Document technical ETL specifications for a data warehouse. Perform periodic code reviews and test plans to ensure data quality and integrity.
• Strong analytical and interpersonal skills
• Enthusiastic, highly motivated and ability to learn quick
• Ability to work through ambiguity in a fast-paced, dynamically changing business environment
• Ability to manage multiple tasks at the same time with minimum supervision
• Bachelor’s degree from an accredited university or college in computer science.
• 3+ years’ experience in the data warehouse space.
• 3+ years’ experience working with large scale ETL systems (implementation and maintenance, CDC/Event-driven architectures).
• 3+ years of experience building clean, maintainable, and well-tested code.
• Experience dealing with large databases
• SQL proficiency
• Databases such as MemSQL, MySQL, Postgres
• Bonus points for background in data science, analytics, or data mining
• Experience in any of the following is preferred but not required: Spark, Dask, Jupyter
• Excellent communication skills to collaborate with stakeholders at all levels of the company.
• Proven ability to learn quickly, work independently, and adapt to change in a fast-paced environment
• High-level written and verbal communication skills.