Lead Software Engineer
The Group
The Morningstar Direct group is the home of Morningstar's flagship product (https://www.morningstar.com/products/direct). We work to serve the needs of professional investors in Wealth and Asset Management firms. Morningstar Direct connects the product, research, business intelligence, marketing, and wholesaling groups within these firms, and drives efficiency across their primary manufacturing, distribution, and marketing workflows by leveraging Morningstar's data, research, analytics, and reporting capabilities.
We love working with technology that is changing the way quantitative analytics is being done in the world. We believe in providing users access to Morningstar's data via tools and programming languages that are already loved and used by the data science community. Our vision is to "stand on the shoulders of giants" and use many of the open-source data analytics technologies to build our platform. You will dive deep into open-source software projects and learn how they are used in financial engineering.
We are deeply inquisitive; we do not take "that's just the way it's always been done" or "that's just best practice" as valid answers and instead seek to fine-tune our product development process for maximum impact. We are empowered professionals who are given problems to solve and not tickets to implement. We value team productivity over individual productivity and this culture of "giving" means we enjoy and highly value collaborating with our teammates.
The Role
Our team is building the next generation of analytical tools (called Analytics Lab Notebooks (https://www.morningstar.com/products/direct/analytics-lab). We are building these tools by collaborating with our Manager and Quantitative Research teams who use popular data science platforms/libraries like Jupyter, Python, Pandas, Plotly, Altair, and other open source offerings. By sharing the same tech stack/language and leveraging open source technologies we plan to deliver feature-rich analytic tools to our clients in a shorter timeframe.
Responsibilities:
- Advance the Direct user experience by building new analytic tools that leverage popular data science platform technologies
- Evaluate data visualization platforms and how they can be integrated into our user experience
- Partner with the quantitative analysts, data scientists, product managers, and software engineers to help shape the product and content.
- Act in a mix of individual contributor hands-on engineering tasks as well as managing/mentoring engineers.
- Apply DevOps practices in area of continuous and automated deployment
- Technical product ownership and responsibility to adhere to established guidelines through peer reviews for design and code, unit test results and deployment process for improving development team productivity.
Qualifications:
- Friendly and enjoys working in a collaborative team with excellent spoken and written communication skills. Humble, honest, and to the point.
- Deep experience with at least one programming language.
- Solid understanding of computer science fundamentals: data structures, algorithms, design patterns.
- Experience with engineer practices such as writing design documents, performing code reviews, pair programming, taking part in agile product development processes.
- Development experience with HTML5, JavaScript and CSS3
- Familiarity with Data Science platforms/tools: Jupyter, Python, and Pandas preferred (or other programmatic data analysis tools; R, Julia, MATLAB, SAS, etc)
Nice to Haves - Not Requirements!
- Managing/leading a team of engineers.
- Hands of experience with Flask, Django, or other web app development frameworks.
- Experience with Python dashboarding frameworks such as Voilà, Plotly Dash, Streamlit, or Panel a plus.
- Experience building CI/CD pipelines using tools such as Jenkins, Teamcity, or CodeDeploy.
- Experience with Docker, Kubernetes.
- Experience with infrastructure as code tools. Terraform is a plus, but any tools in this area such as CloudFormation, Ansible, Chef, or Puppet.
- Experience with AWS data lake tools, such as Lake Formation, Athena, and Glue
- Experience working with cloud services, preferably AWS
- Experience with databases such as Postgres, Redshift, MS SQL
- Familiarity with JavaScript frameworks like Vue, React, Ember, Angular, etc
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