Reporting into Paddle's CTO, the Data Engineering Team Lead is expected to demonstrate technical leadership, inspiring team management and accountability for the delivery of technical solutions to implement Paddle’s data systems. You will be part of the Engineering leadership team, work as part of the larger engineering team and support analysts decentralised across the organisation.
As the SaaS space expands, there’s more potential than ever for growing software companies.
Having a great product is only part of the journey. B2B SaaS companies today face endless competition, live or die by customer acquisition costs, have to earn customer loyalty every day, need to operate across borders, and must navigate increasingly complex regulations.
Paddle alleviates this pain with its industrialised Revenue Delivery Platform that makes it easy for SaaS companies to respond faster and more precisely to every growth opportunity across acquisition, renewals and expansion.
Our all-in-one platform is purpose-built for modern SaaS execution and already powers growth for over 2000 software companies, globally. Our Revenue Delivery Platform integrates checkout, payment, and subscription management, making it easy for businesses to activate new business models, enter new markets, turn on new offerings, and renew subscriptions without friction and we handle compliance globally, so our Sellers always operate with full integrity.
About the Team:
The Data Engineering team at Paddle is a new team responsible for building and owning the core data infrastructure and data processing pipelines supporting Paddle’s data products and business insights. The team supports all areas of the business from both from a data warehousing perspective as well as helping deliver solutions on our data streaming infrastructure. The team will initially be made up of two individuals but will scale in subsequent months. It is a huge opportunity to build something from ground up.
Reporting into the CTO, the Data Engineering Team Lead is expected to demonstrate technical leadership, inspiring team management and accountability for the delivery of technical solutions to implement Paddle’s data systems. You will be part of the Engineering leadership team, work as part of the larger engineering team and support analysts decentralized across the organization.
What you’ll do:
- Accountable for data infrastructure, data architecture as well as data services and products.
- Build and improve engineering practices & processes - aligning and contributing to the ones set across Paddle Product Engineering.
- Lead, nurture and manage high performing engineers.
- Engagement of direct line reports, ensuring expectations are set and understood.
- Recruitment and Onboarding.
- Leverage your experience and skills to assist your team in establishing the best architecture.
- Work with team leads from Product Engineering and SRE teams to standardise our data engineering tech stack, establishing best practices and developing generic software components that can be adopted in multiple projects continuously improve the discipline of product engineering.
- Liaise with the commercial and finance operational team leads to identify requirements and develop the necessary data solutions to deliver against those requirements.
- Practise DevOps, you’re responsible for getting your code to production and maintaining it.
- Explore and use the right tools for the job, backing your choices constructively.
- Help design a stable platform to support phenomenal growth.
We'd love to hear from you if you have
- A proven track-record of leading high-performing teams of engineers or you are a seasoned engineer who would like to take on both tech leadership and line management of a data engineering team. We are open to software engineers who have a passion and interest in data and would like to make that transition.
- Solid development background with Python.
- Good experience working with IaC tools (we use Terraform).
- Experience designing and building systems to handle high traffic at scale in a cloud-based environment in AWS. Experience with Jenkins, Kibana, Grafana & Prometheus highly desirable.
- Good understanding of data modelling. Experience with Redshift and/or Snowflake is a plus.
- Experience with batch processing frameworks, preferably familiarity with DBT, Apache Airflow, or similar a plus.
- Experience with Fivetran, Matillion, Stitch, or similar (we use Fivetran) a plus.
- Experience with message brokers and stream processing technologies e.g. Kinesis
Why you’ll love working at Paddle
We are a diverse team of around 120 people and care deeply about enabling a great culture which is inclusive no matter your background. We celebrate our diverse group of talented employees and we pride ourselves on our transparent, collaborative, friendly and respectful culture.
We offer a full slate of benefits, including competitive salaries, stock options, pension plans, private healthcare and on-site coaching sessions. We believe in flexible working and offer all team members unlimited holidays and 3 months paid parental leaves regardless of gender. We value learning and will help you with your personal development where we can — from constant exposure to new challenges and annual learning stipend to regular internal and external training.
Our mission is to help software companies succeed — enabling them to focus on creating products the world loves. Thousands of companies rely on our revenue delivery platform to sell their software products globally, as well as our powerful analytics and marketing tools to understand and grow their businesses.
Our vision is to become the platform that all software companies use to run and grow their business. We aim to replace a fragmented ecosystem of specialised tools with a unified platform that removes the complex burden that comes with running a software business, whilst also providing unparalleled insight to help them grow faster.
Deloitte Fast 50 named us amongst the fastest growing software companies in the UK four years running, and we’ve raised over $93m in funding from incredible investors such as FTV Capital, Kindred, Notion, and 83North