Analytics Engineer

at  SafetyCulture

ANALYTICS ENGINEER

Sydney
Operations – Data Analytics /
Full-time Permanent /
Hybrid
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SafetyCulture is a customer and product-led SAAS company, our mission is to help working teams get better every day, our technology platform and products give front line workers a voice and leaders the visibility to make smart decisions when driving safety, quality and continuous improvement.
We’re seeking an Analytics Engineer to part of the Internal Analytics team, you’ll use your skills to help us understand what’s working for our customers, what’s not, and what we need to do next to improve our products and grow our business.
The Analytics Engineer at SafetyCulture is responsible for empowering the Data Analytics team with the right data model for their needs, enabling them to find insights that can make a change to SafetyCulture as a company. This is a key role in keeping the organization’s knowledge organized, easily accessible, and accurate.
The Analytics Engineer will collaborate with different stakeholders across the business (Finance/Marketing/Sales) to turn billions of rows of source data into highly valuable datasets and data products. SafetyCulture is expanding rapidly which requires the Analytics Engineer to integrate different systems and datasets from differing business contexts.

WHAT YOU WILL BE DOING:

• You will apply software engineering methodologies to our analytics stack;
• Ensure that our datasets will be maintained with the right level of testing and validation for data quality;
• Maintain, operate and tune the infrastructure (dbt, Redshift, Airflow, Hightouch, Fivetran);
• Work closely with Data Analysts to support them in their daily work to ensure our datasets can support the business in what they’re trying to achieve;
• Promote our data warehouse has the central source of truth within SafetyCultureBuild a data-driven culture across the business;
• Guide business users on how to use our data platform.

THE SUCCESSFUL APPLICANT WILL BRING TO THE ROLE:

• Experience in dealing with very large datasets in a cloud platform (Preferred AWS);
• Experience on modern data warehouses technologies (Redshift, Snowflake, BigQuery)Advanced SQL, Python/Jinja coding experience;
• Knowledge of data modelling methodologies (Kimbal/Inmon/Data Vault/Activity Schema)
• Knowledge of data warehousing principles e.g. DAG architecture, schemas, performance and optimisation;
• Understanding of the differences between ELT/ETL, and the implications on the analytics team and the business;
• Strong communication and stakeholder management skills with the ability to regularly influence and guide decisions;
• High level of comfort with ambiguity, and ability to work in a fast-paced, agile environment in which you rapidly adapt and learn for any given business problem.