Senior Data Engineer

What do we do?

Paddle offers SaaS companies a completely different approach to their payment infrastructure. Instead of assembling and maintaining a complex stack of payments-related apps and services, we’re a Merchant of Record for our customers. That means we take away 100% of the pain of payment fragmentation. It’s faster, safer, cheaper, and, above all, way better. 

We’re backed by investors including KKR, FTV Capital, Kindred, Notion, and 83North and serve over 3000 software sellers in 245 territories globally. 

The Role:  

You will be responsible for delivering technical solutions to implement Paddle’s data strategy. You'll work with cross-functional teams to build practical solutions, create secure data pipelines, and prepare data for analysis.

We are looking for an analytics-focused engineer to build data models and utilise data insights to drive decision-making and optimise processes throughout Paddle.

What you'll do: 

• Work with cross-functional teams to understand their data requirements and develop practical solutions that meet those needs.

• Assist internal teams with operational data support requests.

• Build and maintain efficient and secure data pipelines to ensure smooth data flow across the organisation.

• Use data transformation techniques, including advanced aggregations and data wrangling methods, to prepare data for analysis.

• Ensure data accuracy, completeness, and consistency by implementing quality checks and resolving issues.

• Implement DevOps practices to deploy and maintain the code in production environments.

• Stay up-to-date with the latest industry trends, tools, and technologies related to data engineering.

We'd love to hear from you if you have:

• Good knowledge of database management systems such as SQL, NoSQL, and columnar databases.

• Solid understanding of data modelling, data warehousing, and ETL concepts.

• Experience with cloud-based platforms such as AWS, GCP, or Azure

• Experience with Fivetran, Meltano, Airbyte, Stitch, or similar data integration tools.

• Familiarity with BI tools such as Looker, Tableau, Sisense or comparable.

• Familiarity with DBT, Apache Airflow, or comparable is desirable.

• Strong attention to detail to identify and resolve data quality issues.

• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.

Everyone is welcome at Paddle

At Paddle, we’re committed to removing invisible barriers, both for our customers and within our own teams. We recognise and celebrate that every Paddler is unique and we welcome every individual perspective. As an inclusive employer, we don’t care if, or where, you studied, what you look like or where you’re from. We’re more interested in your craft, curiosity, passion for learning and what you’ll add to our culture. We encourage you to apply even if you don’t match every part of the job ad, especially if you’re part of an underrepresented group.

Please let us know if there’s anything we can do to better support you through the application process and in the workplace. We will do everything we can to support any accommodations needed. We’re committed to building a diverse team where everyone feels safe to be their authentic self. Let’s grow together. 

Why you’ll love working at Paddle

We are a diverse, growing group of Paddlers across the globe who pride ourselves on our transparent, collaborative and respectful culture. 

We live and breathe our values, which are:

Exceptional Together

Execute with impact

Better than Yesterday

We offer a full suite of benefits, including attractive salaries, stock options, retirement plans, private healthcare and well-being initiatives. 

We are a ‘digital-first’ company, which means you can work remotely, from one of our stylish  hubs, or even a bit of both! We offer all team members unlimited holidays and enhanced parental leave. We invest in learning and will help you with your personal development via constant exposure to new challenges, an annual learning fund, and regular internal and external training.