Data Engineer

What we do at Codat

Our mission is to make life easier for small and medium sized businesses, the backbone of our global economy. 

We do that by working with fintech companies and financial institutions to help them connect into the systems their small business customers use. With this connectivity, our clients are building next generation products to take the friction out of running a small business, from business management software to alternative lending and corporate cards.

Codat is a Series C-funded company, backed by some of the leading investors and most successful tech companies in the world, including J.P. Morgan, Shopify, Plaid, PayPal Ventures, Amex Ventures, Index Ventures and Tiger Global. We have offices in London, New York, Sydney.

We live by our values of being united as a single team, building a product that is useful to our clients and their customers alike, and bringing a focus and urgency to our work that makes us unstoppable.

What you will be doing

We are looking for a Data Engineer to help us build powerful data infrastructure and advanced analytics to support Codat’s decision making as we enter our next phase of growth. There is an immense amount of opportunity to plan and build pipeline architecture, own data sources, and execute business-critical analysis. As the pipeline matures, there is also significant opportunity to expand the role’s responsibilities from Data Engineering to Data Science depending on the candidate.

Key responsibilities:

• Be a critical member of a tight-knit and high-performing Data and Analytics team
• Plan, build and maintain Codat’s internal data infrastructure, specifically:
• Be responsible for the ingestion of raw data sources
• Be responsible for the enrichment and standardisation of raw data across multiple sources
• Be responsible for setting a data pipeline roadmap
• Develop Codat’s data strategy, shaping the way the organisation consumes data
• Prioritise the most critical needs of the business and deliver data and analytics to support those areas
• Act as a spokesperson for the Data and Analytics Team internally, while building wider understanding and appreciation of data resources within Codat
• Provide technical expertise and training on analytical best practices to the data and wider business teams
• Lead efforts to migrate decision-making away from ad-hoc processes to being fully-underpinned by intelligent data-driven models

Our values

No matter what we’re doing – whether we’re speaking to customers, partners or to each other – we live by our values.

We believe in delivering useful technology that solves real problems for real businesses.  We have a real want to do the stuff that isn't always “cool” but makes a difference.

We believe that the people in the best teams push and enable each other to excel.  We’re united and we have each other’s backs – when something goes wrong, we don’t blame, we work together to fix it. Transparency in our interactions is critical to drive towards our goals as a team. 

We openly share all information with all colleagues by default, unless we have a very good reason not to. We embrace differences of opinion to end up with better outcomes.  We don’t let our egos win.

We believe that an unstoppable drive towards a single, clearly stated goal is the best way to build great things.  We are biased towards action – we make informed decisions and then we act. We inspect and question the status quo with curiosity, unafraid to ask the hard questions. There is no such thing as an impossible problem, just a great challenge to sink our teeth into.

Minimum qualifications 

• Demonstrably strong technical skills, with a focus on Python and SQL
• 3+ years experience working in a data engineering environment at a start-up or scale-up
• Familiarity with key engineering concepts such as data warehousing and ETL/ELT processes
• Professional drive and intellectual curiosity
• Excellent communication skills and EQ
• Experience with delivering projects against tight deadlines while maintaining a balance between programmatic rigor, speed of execution, and long-term planning
• Technical skills: Python, SQL

What excites us

• Experience in owning data pipelines and living the life of a business-critical data engineer
• Data Science or quantitative skills learned either through an academic qualification or professional experience
• Drive, enthusiasm, intellectual curiosity, willingness to learn
• Software familiarity: Salesforce, Microsoft Azure, Node, Fivetran, Pyspark / Databricks, dbt, Looker, Snowflake

If you are excited about applying for this role but aren't certain you meet 100% of the criteria, we'd still love to hear from you