About the Client:
Australian medical device company that manufactures the Trophon system — a global standard for high-level disinfection of ultrasound probes. The company operates globally, with primary commercial presence in the US, Canada, and Australia/New Zealand.
Role Overview:
You will work on the Raw-to-Validated layer of the dbt project, owning the most complex and high-value data modeling tasks. This includes building and maintaining conformed customer (NPI Type 2 as the canonical key, Salesforce–D365 crosswalk, IDN hierarchy), product, and territory dimensions, as well as managing SCD Type 2 history, deduplication, and cross-system reconciliation. You will perform deep technical work in a primarily asynchronous environment, based on requirements from the Tech Lead and Analytics Engineer.
Responsibilities:
- Build dbt staging models with schema and freshness tests, maintaining source-aligned structures without business logic;
- Develop conformed dimensions (Customer, Product, Territory) using SCD Type 2 history, ensuring cross-system reconciliation and unified ID hierarchies across Salesforce, D365, and IDN;
- Engineer comprehensive dbt test suites for data quality, referential integrity, and cross-system reconciliation to ensure alignment with D365 financial totals.
Requirements:
- Expertise in dbt Core, including daily development of models, tests, and documentation, with hands-on experience managing snapshots and incremental materializations;
- Proficiency in Snowflake, including daily hands-on experience with schemas, stages, and the application of Snowflake-specific SQL optimizations;
- Expert-level SQL proficiency, with deep experience in crafting complex joins, window functions, and CTEs to implement advanced SCD Type 2 logic;
- Strong mastery of Kimball methodology, with proven experience in designing fact tables, conformed dimensions, and various slowly changing dimension (SCD) patterns;
- Strong command of Git and Bitbucket workflows, including feature branching and rigorous PR processes;
- Strong background in data quality engineering, including the implementation of dbt tests, data contracts, and freshness checks to ensure high-integrity datasets;
- Upper-Intermediate level of English and higher.
Nice to Have:
- Experience with ERP data (D365, SAP, Oracle, QAD);
- Experience building customer crosswalks / master data reconciliation;
- Experience with healthcare data (NPI numbers, facility hierarchies).
Our benefits:
- Professional and career growth promotion;
- Competitive salary;
- Paid vacations and sick leaves;
- Internal Medical Program;
- Program for veterans (which includes mentorship, an accessible office for individuals with disabilities, legal support, and additional benefits);
- Flexible working hours;
- Regular corporate social activities;
- Regular technical training at our office;
- English courses;
- Gym, etc.
