Databricks - dbt Data engineer

 

 

Databricks SME - 5+ Years of Databricks Experience - Hands-on technical lead responsible for solution architecture, delivery planning, estimations, work management, and mentoring, coordination with advanced-level data modeling and DBT skills, while actively leading and assisting with pipeline development, DBT model conversion, refactoring efforts, engineering standards, and technical delivery. Dimensional Modelling expertise.

 

Data Engineering Solutions - 10+ Years of Data Engineering Experience - Deep experience optimizing Gold-layer Delta tables and dimensional models specifically for high-performance Power BI consumption (e.g., minimizing complex downstream DAX through upstream transformations).

 

Financial Data - Familiarity with Oracle Fusion ERP data structures, BICC extraction patterns, or complex financial data domains.

As part of the Project Independence (PI) implementation, driven by the migration of the organization''s on-premises Oracle database platform to Oracle Fusion Cloud, the Data Engineering (DE), Business Intelligence (BI), and Quality Assurance (QA) teams are executing a strategic initiative to ingest Fusion data on 15 minute intervals, model the data and progress things through the medallion layers, adapt or rewrite existing tables/models, and migrate datasets, products and Power BI reports from legacy financial models to the new fusion models.

 

The differentiator is that the Lead owns technical implementation / influence architecture, dependencies, planning, estimation, execution team leadership, and data modeling, while the other three engineers are primarily focused on pipeline development, DBT model conversion/refactoring, and delivery execution and BI Semantic Model refactoring oversight

All Data Engineers should have:

•Very Strong Databricks Lakehouse principals and experience

•Hands-on Unity Catalog experience

•Experience developing Spark Declarative Pipelines (Lakeflow/DLT , autoloader)

•Strong pipeline development capabilities

•Deep Experience with DBT model development, conversion, and refactoring

•Exposure to Power BI and analytics consumption patterns

•Working knowledge of Azure DevOps CI/CD pipelines

•Familiarity with metadata-driven frameworks

•Exposure to code generation and agentic engineering patterns

•Strong SQL and PySpark development skills

 

Required Non-Technical Skills

Collaboration

•Ability to work closely with BI and QA teams

•Strong partnership mindset

•Ability to participate in technical design discussions

•Effective stakeholder engagement

•Routinely partners with QA to define testing criteria for data accuracy and proactively updates Project Management on technical blockers, delivery timelines, and sprint progress without requiring micromanagement.

 

Communication

•Excellent verbal communication skills

•Strong written communication skills

•Ability to explain technical concepts clearly

•Ability to communicate blockers and dependencies effectively

 

Ownership

•Strong accountability

•Ability to work independently

•Takes ownership of assigned deliverables

•Drives issues to closure

 

Risk Management

•Raises alarms early when risks are identified

•Escalates blockers appropriately

•Proactively identifies project dependencies

•Communicates schedule or quality risks effectively

Problem Solving

•Strong analytical skills

•Root cause analysis capabilities

•Ability to investigate data discrepancies

•Solution-oriented mindset

 

Critical Hiring Requirement

These roles are intended to accelerate delivery immediately and are not entry-level or development positions. Candidates must have proven, hands-on experience with Databricks, Unity Catalog, Spark Declarative Pipelines (Lakeflow/DLT), DBT development and refactoring