Team Lead Data Engineering

OTA Insight is a commercial platform for the hospitality industry (our clients are AirBnb property owners, individual hotels and major chains like Hilton, Accor, etc.). These are exciting times at OTA Insight: we recently raised another round of funding ($80 million) and we have welcomed two new companies, Transparent and Kriya, to our organisation that will expand our product portfolio! To accomplish our ambitious plans we are growing our Engineering team and Data Engineering has a crucial role to play. So, are you ready to have a big impact in a fast-growing scale-up?

We are looking for a Lead Data Engineer who is passionate about scalable data architectures, cloud technology, complex data transformations, and handling large data streams on the fly, and wants to see their work translated into real life applications that impact 100.000’s of hotels worldwide.

About the team & the role

The OTA Insight Data Engineering team in Ghent is the gatekeeper to our vast datasets. We are the go-to team for any new feature development that requires adaptations to the way we store, model and aggregate our data. The team works in close collaboration with our Product team, as well as a highly talented group of software engineers and data scientists to drive initiatives forward.

In this skilled team you’ll be trusted to:

• Implement, maintain and improve streaming and batch data processing pipelines.

• Set up and maintain infrastructure & tools to support our data processing pipelines.

• Research and test data processing methodologies, tools and frameworks.

• Actively contribute to the observability & testability of our data pipelines.

• Be part of the product scrum-teams, to tackle data storage, modelling and transformation problems related to new feature developments.

As a team lead we expect you to:

• Manage a team of data engineers and provide guidance to increase the efficiency, stability, deliverability, and maintainability of everything your team produces.

• Plan and prioritise your domain roadmap in close collaboration with both external stakeholders within the engineering department and senior members of the team. Engage in architectural discussions.

• Continuously look for ways to improve the development process within your team, e.g. on coding best practices, reviewing and testing process, support process,...

• Regularly follow up with team members and help them grow and develop within the organisation, take part in various talent enablement conversations throughout the year and resolve employee grievances.

• Keep peers and leadership informed about progress and blockers on technical and people subjects.

Technologies you’ll work with:

Google Cloud Pub/Sub, BigTable, BigQuery, Dataflow, Kubernetes, Python

 (feel free to ask us why these are the best fit for us)

Benefits of working at OTA Insight

• The opportunity to shape the products that more than 75.000 users rely on world-wide;

• The chance to grow and evolve the data culture at a fast-growing scale-up;

• A flexible working environment where you can work from home or at one of our offices;

• Two annual Detox Days, on top of your personal holidays, when we take some time away from our computers with the entire company;

• A choose-your-own transportation budget should you choose to come to the office;

• A highly competitive compensation package.

We are looking for:

• 5+ years of experience in a data engineering related position;

• Professional experience in Python;

• Knowledge of one or more cloud database solutions like BigQuery, Snowflake, BigTable, DynamoDB, Spanner,...;

• Experience with microservice architectures and one or more data streaming systems like Kafka, Google Cloud Pub/Sub or Amazon SNS,...;

• Desire to continually keep up with advancements in data engineering practices;

• You have played an active role in the data research phase of new projects, and actively contributed to the idea generation process;

• You are always curious about how a technology works under the hood, in order to make a proper assessment of what the ideal use-case for the technology is and understand its limitations;

• Experience in the serverless offering of cloud providers like e.g. GCP or AWS;

• Fluent in English.