Data Success Engineer

Level Open

CapacityFull time

TypeEmployee

LocationNew Zealand (preferably Dexibit's Auckland office, open to domestic remote)

Reports to Chief Technology Officer

Who we are

Do you love dinosaurs and data? We are Dexibit, and we do We're a Kiwi start up pushing the visitor attractions industry to be data driven. We empower our customers by democratising data and unlocking the insights within. We're a diverse, empowered team who have collected a fair few awards in our time from HiTech, NZIBA, TIN and more Our customers include famous international brands like the Smithsonian, alongside local favourites such as MOTAT and Auckland Zoo.

What we do

We have a small but mighty data success team at Dexibit. Our mission is to support our business by being at the intersection of data engineering, product development, and customer success, ensuring we deliver real world value for our customers.

We work with diverse datasets. From transactional ticketing and sales tables through to demographics and streams of weather and calendar events. You will have strong business acumen and an almost forensic mindset to connect and uncover the untold stories behind our customer's data.

Our technical stack is equally diverse. From gnarly custom Airflow scripts and S3 buckets to state of the art DuckDB and Databricks pipelines. None of this should bother you, because you enjoy working with technologies and systems new and old.

Engineering at Dexibit

You'll have at least 1 year of experience in a technical role with exposure to business-focused data analytics, software engineering, and customer support.

Most importantly, you must demonstrate an ability to work in a collaborative environment, be an organised and confident problem solver and be able to communicate complex ideas clearly in a distilled, meaningful manner.

You'll need:

• Excellent written and verbal communication
• Bachelor's degree or higher (in an engineering, science, or related discipline)
• Strong data analytics development experience using Python and SQL
• Familiarity with consuming APIs, writing API integrations, and web scrapers
• Familiarity with data platforms like Snowflake, Databricks, BigQuery, Redshift; transformation tools like dbt; and orchestrators like Airflow, Dagster, and Prefect
• Experience with curating, modeling and cleaning data from a variety of structured and unstructured sources
• Comfort in communicating directly with customers or vendors
• Interest in machine learning and generative AI
• Most importantly, a great attitude and a growth mindset

Key responsibilities/acccountabilities

• Onboarding new customer data and analysing new datasets to build up a suite of key analytics insights.
• Developing data pipelines and data transformations using Python and SQL
• Supporting existing third party integrations and creating new ones by interfacing with APIs, databases, and other data sources
• Assisting to resolve technical customer issues and requests together with customer success and product engineering
• Manually updating customer data and integrations – we're in a transition phase where sometimes some manual data manipulation (e.g. uploading specific data from different sources) is still necessary for our customers to get the most out of our product
• Elaboration of our processes – in collaboration with Product and Success, you will help define and implement Support workflows
• Sharing customers' needs with Product – you'll gain a deep understanding of our customers' pain points and needs while interacting closely with them and will be able to share these back to help shape our product priorities.

Even if you can't tick all the boxes we still encourage you to apply Dexibit recognises all our team as diverse and unique individuals, and we'll meet you where you're at.