Role Overview - StaplesWe are looking for a Data Engineer to design and build a robust set of tools and pipelines to support data analytics efforts. You'll manage and optimize our core infrastructure by creating and maintaining data pipelines. You will work with other engineers and analysts from to design, implement, and maintain a data ecosystem that delivers actionable insights to make key business decisions. You have technical chops but can also work independently to prioritize issues, work within ambiguity, and manage conflicting deadlines. You are creative, data-driven, results-oriented, and eager to help us solve data problems of varying complexities. We are open to a Senior or Principal title as well, based on experience level.
Responsibilities- Develop technical solutions using proven techniques in data and analytics processes
- Develop, prototype, and build frameworks based on open source and commercially available tools
- Orchestrate and maintain data pipelines that meet security standards and ensure the integrity and quality of data
- Demonstrate a passion for serving the needs of internal and external customers by enabling them with self-service reporting tools and analytics capabilities
- Drive the execution of data initiatives that provide key performance metrics
- Understand the data related challenges, nuances, and requirements to identify and recommend the optimal technical approach
- Train and educate team members as well as stakeholders about best practices in data engineering and governance
- Collaborate closely with the engineering and devops team to implement DataOps, thus reducing our analytics development cycle
- Research and improve our data platform to ingest, process, transform, and distribute insightful data to our audience ranging from executives, analysts, and engineers to customers, vendors, and partners
- Evangelize data driven culture by breaking down silos and encouraging data sharing
Ideal QualificationsThe qualifications below are ideal, but not all are required. We encourage candidates to apply if they satisfy some, but not all of the qualifications.
- 3+ years of hands-on experience in data engineering for a SaaS company or a mature startup
- Proven experience working with various tools but more importantly, familiarity with how to best assemble and deploy production ready data stack to any cloud environment
- BS in a quantitative or scientific field such as computer science, computer engineering or equivalent experience
- Experience in applying agile software development approach - Git, CI/CD, Jira, etc - to data engineering
- Expertise with the Python library
- Exceptional fluency with SQL; you conquered the join venn diagram long ago and have moved on to explaining cost based optimization to your peers on the engineering team
- Some level of experience working in the cloud - AWS, Azure, or GCP
- Experience with ingesting, processing, and visualizing data sources of varying types - structured/relational and unstructured
- Experience in developing, managing, and manipulating large, complex datasets
- Data-driven, detail-oriented individual with excellent storytelling and problem-solving abilities
- Ability to work independently and autonomously, as well as part of a team
- Superb time management, prioritization of tasks and ability to meet deadlines with little supervision
Ideal candidate will thrive in the following culture:
- Must have an obsession for building quality products
- Ability to thrive when there are changing priorities and shifting of gears
- Strong oral and written communication skills
- Must be a team player with a strong, self-managing work ethic
- Must be a self-starter with a passion for data, learning and continuous improvement
