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Portag3 Ventures: Data Engineer

Portag3 Ventures

This is a Full-time position in Montreal, QC posted September 15, 2020.

Portag3 Ventures is looking for our first Data Engineer to spearhead the development of new technology to support our venture business.

As a VC fund, we are an information business focused on investing in information businesses.

We are passionate about supporting our investment operations and decision making with data and technology and would like to invest in building a best-in-class technology stack to do so.As a Data Engineer, you will play a key role in leading the scoping, design and build of our new VC tech platform, which will support key operations such as sourcing (both company and talent sourcing) and data management.We are looking for a rare breed, part-product-manager and part engineer:A (pragmatic) product-oriented engineer, who can help us define the MVP of our VC technology data platform and manage the roadmapA full-stack data engineer, who is excited and willing to roll up their sleeves and help code the first version of the platform.

This is a great fit for someone who loves to build.A natural collaborator, who can work with various stakeholders across our fund from the investment team to finance (e.G., “users”)For the right individual, we imagine this role could evolve, over time, into a broader technology leadership role at our fund, including conducting technical diligence on new investments and advising our portfolio companies on technical matters.Our data and technology platform will have several parts, which link directly to core functions within our VC investment process:Company sourcing (initial scope of the MVP will focus here): Increase the universe of companies that we see in our sourcing processTalent scouting: Track key talent movements in the fintech spaceKey responsibilities of the data engineer include:Serve as product-manager and work with wider Portage Ventures team to define requirements for MVP of data platformRoll-up sleeves and help to code up first version of MVPManage scope and build of MVP within budget and timelinesHire team and add capabilities over timeKey characteristics :Builder / Doer –Excited to roll-up sleeves and build first version of MVP.

Can make trade-offs in tech stack selection.Architecture / Systems Thinker –Systems thinker with the ability to map out system design / architecture and how it all comes together (architecture not features).Simplification –“Invents and simplifies.” Clear thinker who can simplify a complex problem.

Will be important as we move towards an MVP.Prioritization & Problem Solving –Ability to decide what to do first and make tradeoffs/ There are a million potential starting points and a top-level leader helps the team find the right one and order the problem from there.Technical experience:Exposure to the following technologies and approaches is a nice-to-have:Google Cloud Platform: IAM, BigQuery, Cloud DataflowPython Data Integration and DevelopmentData centric frameworks: Numpy, Pandas, Scikitlearn, TensorflowExperience building serverless functions to source dataExperience with data pipeline managementData architecture experienceBaseline Requirements:Bachelor’s degree in a quantitatively oriented field (e.G., computer science, math / statistics, engineering)5-10 years experience as a software and / or data engineerRelevant experience includes: Piping, extracting, scraping and joining disparate data sets (both public and private data); drawing conclusions from noisy / incomplete data-setsTrajectory / worked for firms with strong engineering and technical pedigree.Demonstrated ability to ship product and operate in a fast-paced environmentUnderstanding of data science / statistical modellingTeam & Cultural FitNon-dogmatic and flexible mindset – open to building or buying different componentsA natural collaborator, who can work with various stakeholders across our fund from the investment team to finance (e.G., “users”)