Us: Default alive startup of 60+ people. Remote team, mainly based in the UK. YC alumni. Creating a web-based platform for behavioural research. 3x yearly growth, all driven by word-of-mouth.

We’re on a mission to connect people around the world to make trustworthy data more accessible and facilitate world-changing research.

You:  An experienced analytics engineer or data engineer who is a DBT expert and has a passion for empowering self-serve analytics.

Location: Remote within the UK (and Europe)

The tools: SQL, DBT, Snowplow, Redshift

Competitive day rate

As a complex marketplace platform with a strong focus on data, we know we're sitting on a trove of information that can take our product, and world-class research, to the next level. We're looking for a Data Analytics Engineer to transform our raw (and sometimes messy) data into structured, intuitive datasets which empower crucial insights across the business.

This will involve building reliable SQL-transformation pipelines, as well as wrestling with intriguing data-related-challenges fundamental to scaling our business. For example: leveraging the data in our Snowplow web-tracking model to determine which visitors to our website are returners and which are new. Or working alongside our marketing team to model multi-touch attribution.

The ideal candidate will be able to think about data-usage from the perspective of the end-user, and combine software engineering approaches with analytics know-how to create scalable ELTs. You should have strong experience with SQL and be comfortable with a scripting language (Python, etc). Flexibility and willingness to learn are key: Prolific is evolving continuously and you'll have the opportunity to shape your role in response to changing data-demands. You'll also be able to learn about all layers of our data stack, from product-driven event analytics, to data storage, modelling and BI tools.

You'll be part of a growing and talented team of data analysts, data engineers and data scientists. We'll support each other, upskill each other, and provide a place to brainstorm and problem-solve together. We hope you'll also be a mentor to your teammates: boosting everyone's standard of data-software engineering.

At Prolific, projects are delivered using squads: small multi-disciplinary teams of 3-7 people (engineers, product designers, data analysts, product managers, etc). Squads are problem-focused and work on high-level objectives, e.g. our Growth Squad is working hard to ramp up data-driven content marketing, and deeply understand potential users purchase-decision journey. Squads use 6-12 week cycles to meet their objectives, with continuous delivery throughout the cycle.

Since data is a cross-squad discipline, we've founded the "data-chapter" to provide a place for all data experts to work closely together, share processes, and collaborate on core infrastructure. As a Data Analytics engineer, you'll be a core member of the data-chapter, splitting your time about 60/40 between core data-infrastructure work, and more bespoke projects for squads.

Deep work is valued throughout the company. We favour async communication (like Notion) over Slack. When we need to communicate in real-time we try to cluster meetings together to give everyone bigger blocks of interruption-free time.

Continuous learning and development is strongly encouraged. Everyone gets a personal development budget which they can put towards things like books, courses and conferences, and reserve times every fortnight for learning new things or working on creative side-projects.

We’re aware of the challenges of being a remote worker and work hard to foster team spirit. We encourage remote chats over coffee with colleagues and have regular team meetings to keep everyone up to date with goings-on across the company and introduce new joiners.

We believe that we are in the process of successfully building a company that people enjoy working for. Our employees should feel valued, supported, and fulfilled. We know that there’s always more that we could be doing and have regular conversations about what we can improve. Everyone’s opinion is important and all input is taken on board.

We use Snowplow to collect event data, Stitchdata to ETL data from our production MongoDB and secondary data sources, AWS Redshift as a central store and source-of-truth for all our business data, and DBT for data modelling, scheduling SQL, and validating the data in our warehouse. We use Metabase as our primary BI tool and JupyterHub as a central workspace for analysis and deeper exploration of our data.

What you'll be doing:

• Migrating, consolidating, and extending our SQL transformations in DBT while ensuring that our business insights are drawn from reliable, correct and easily interpretable datasets.
• Implementing and optimising data models to unlock the potential of our data.
• Working with our product teams to implement new event tracking, user-stitching, and marketing attribution.
• Playing a key role in building a clean and extendable codebase for data
• Sharing knowledge and best practices with a growing data community across Prolific

Minimum requirements :

• Experience writing high-quality, maintainable SQL
• Experience with DBT
• Knowledge of data pipeline best practices.
• Knowledge of SQL assertions and testing

Nice to have:

• Experience with Redshift/AWS
• Knowledge of/experience working with Python
• Knowledge of/experience working with Dataform

At Prolific, we're changing how research on the internet is done. Our co-founders Katia and Phelim started by building a marketplace that connects researchers from both Academia and industry with instant, high quality, global research participants. Now, as a growing team, our bigger vision is to build the most powerful and trusted platform for behavioral research.

We were in Y Combinator's Summer 2019 batch, we've recently closed a $1.4M seed round, we've been growing 3x a year purely through word-of-mouth, we're already profitable, and we have very ambitious plans.

1st Stage (1.5 - 2 hour interview) we'll deep dive into your past experiences and skills. You'll speak with two to three members of the team and - as always - have an opportunity to ask questions about the role and company.