Senior Analytics 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 and 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 Senior Analytics Engineer to help us deliver business-critical analysis and improve our data infrastructure to support Codat’s decision making as we enter our next phase of growth following our Series C. There is an immense amount of opportunity to design pipeline architecture, solve challenging data integration problems, and execute business-critical analytics. As the organisation grows, there is significant opportunity to develop this role towards Machine Learning (“ML”) and delivering infrastructure to serve ML use-cases.

Key responsibilities:

• Be a critical member of a tight-knit and high-performing Data and Analytics team
• Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making
• Design, build and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources
• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way
• Collaborate with Product and Cross-Functional Teams to migrate decision-making away from ad-hoc processes to being fully-underpinned by intelligent data-driven models
• Design and implement Codat’s next-level infrastructure to serve advanced use-cases (Real-time and ML)
• Develop Codat’s data strategy to shape the way the organisation consumes data

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.

What excites us

• You have previous experience in a similar role with responsibilities giving broad exposure to US issues
• Experience in owning data pipelines and living the life of a business-critical data engineer
• Software familiarity: ELT tools (e,g. Fivetran), dbt, Snowflake, BI tools (e.g. Looker), Pyspark / Databricks, Microsoft Azure,
• Data Science or quantitative skills learned either through an academic qualification or professional experience
• Drive, enthusiasm, intellectual curiosity, willingness to learn
• Bachelor’s degree in Science, Technology, Mathematics, Applied Sciences or equivalent practical experience (focus on Python and SQL)
• 3+ years experience working in a data engineering environment
• Familiarity with key engineering concepts such as data warehousing and ETL/ELT processes
• Professional drive and intellectual curiosity
• Excellent communication skills and EQ
• Technical skills: Python, SQL

What excites us

£75,000-£84,000 / year

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.