Loeb Enterprises invests in promising early stage startups and helps them achieve their potential by providing in-house shared services. Loeb uses a shared services model consisting of a wide variety of teams, including marketing, product, accounting, administrative, data analysis, software engineering, etc. The team is available to assist and consult with all companies within the portfolio.
One of the shared services teams that has proven to be in high demand has been our Analytics Team. As it has grown in size it has been segmented into three main divisions: Business Intelligence, Data Science, and Data Engineering. As more companies have data-driven strategies and products, we are working to scale out all divisions, but most especially the data science team.
As a member of the Data Engineering team, you will have an opportunity to tackle the most difficult data challenges that Loeb Enterprises encounters. You will work with structured and unstructured data, from a wide variety of different industries, involving many disparate tools. A good data engineer is able to discuss solution strategies for how to model and store data, as well as provide support in implementation. The day-to-day work for a data engineer spans activities that range from database administration to full-on development.
Success in the first 90 days
- Understand the datasets for the current portfolio companies that the Analytics team works with, and how these companies use their datasets. One should also understand how these datasets are constructed.
- Become familiar with and engage the project management processes and tools that are used (e.g. Trello, Jira).
- Analyze project roadmaps- request necessary resources and time adjustments based on expected work load to manage expectations.
- Understand and help solve some of the numerous short-term problems that the firm confronts with regards to ETL, data normalization or QA.
- Understand the high-level objectives of the Analytics team as they pertain to the portfolio companies that we serve.
Success in the first 180 days
- Write, test, and commit database or application code to either solve an existing problem or move the needle on one of the outstanding projects.
- Achieve mastery of the data model for 1-3 of the portfolio companies that we work with.
- Have a clear idea of what the business priorities for the portfolio companies are and how your projects relate to them.
- Suggest infrastructural changes where appropriate to facilitate future goals.
- Manage day-to-day operations for 1-2 of our smaller codebases.
- Provide input as to what, if anything, our team culture is lacking.
- Ability to follow instructions, but with the confidence needed to take a solution and “run with it.”
- Discipline – the ability to implement a solution and ensure that it solves the problem.
- Good time-management skills.
- Analytical thought processes- the ability to get to the heart of a problem and organize a structured approach to it.
- Good communication and listening skills. Presentation skills, understanding the audience.
- (preferable)- Degree in computer science, mathematics, science, or engineering.
- A minimum of 2-3 years of experience with at least one programming language and proficiency with at least one other. Should have interest in learning new languages and improving on current ones. Preferred languages include (but are not necessarily limited to): T-SQL, Java, C#, R, Python, and Visual Basic.
- Basic understanding of algorithms, from a practical and theoretical perspective.
- Familiarity with SQL and RDBMS concepts. NoSQL experience is good as well.
- Experience with cloud technologies preferable, with examples of projects run on AWS, Azure, or GCP.
- Experience with source control software, such as Tortoise, Git, GitHub, CVS, or others.
- Experience with ETL and/or architecture projects.