Data Engineer, Specialist

Build ELT pipelines, from source to presentation of data to our internal customers.

Keen appetite for learning as we pick up new tech stacks and help provide solutions to our everyday problems, always keen to be learning along the way under the guidance of our more senior developers and engineers.

Write high quality and readable code, assist with code reviews, provide solution design input, build automated tests, create documentation, and other tasks throughout the development lifecycle.

Collaborate closely with developers, scrum master, and product owner to ensure the data is enabling our client experience.

Identify and help implement continuous improvement of technical standards, methodologies, technologies, and processes.

Own the deployment and operations of the system across environments from development, test, and through to production.

Participate in agile meetings aligned to the scrum framework: sprint planning, daily scrums, sprint review, sprint retrospective.

A bachelor's degree in computer science, STEM or related discipline is a plus, but not strictly required.

1-2 years experience as a data engineer is preferred, though a related discipline will be considered.

Experience with Python and SQL is required as well as a good understanding of working in a cloud-based environment (AWS is preferred).

Experience transforming data using PySpark/Pandas or similar.

Experience building cloud infrastructure using IaC (CloudFormation/Terraform).

An understanding of industry standards and best practices as it relates to development methodology such as testing, code quality and consistency.

Great communication skills: the ability to bridge the gap between the technical and non-technical across various communication channels.

An understanding of agile software development methodology, with scrum framework experience preferred.

A desire to continuously learn and develop yourself in both technical and non-technical skillsets.

Provides advanced data solutions by using software to process, store, and serve data to others. Tests data quality and optimizes data availability. Ensures that data pipelines are scalable, repeatable, and secure. Builds a deep dive analytical skillset by working with higher level Data Engineers on a variety of internal and external data. Why Vanguard? Vanguard is a different kind of investment company. It was founded in the United States in 1975 on a simple but revolutionary idea: that an investment company should manage its funds solely in the interests of its clients. This is a philosophy that has helped millions of people around the world to achieve their goals with low-cost, uncomplicated investments. It's what we stand for: value to investors. Inclusion Statement Vanguard's continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: "Do the right thing." We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard's core purpose through our values. When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success., Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.