Data Engineer - Business Analytics
Analytics
Azure Data Lakehouse
Big Data
Bigdata
Business Analytics
Business Intelligence
Cloud Platform
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Visualization
Data Warehouse
Database
Databases
Databricks
Dataops
Design
Digital Marketing
ETL
Informatica
Information Technology (IT)
Microsoft
Power BI
Power Platform
Reporting and Analytics
Spark
SQL
Visual Design
Job Description
The Data Engineer - Business Analytics role designs, builds, and optimizes analytics-ready datasets within a modern Databricks-based data platform. The work centers on curated Silver and Gold assets in a medallion architecture, with the semantic layer implemented in Databricks.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and curated datasets within the Databricks Lakehouse, including the Silver and Gold layers.
- Develop and manage analytics-ready data models and semantic structures in Databricks aligned to enterprise reporting requirements.
- Transform raw data into business-consumable datasets using standardized definitions, KPIs, and metrics.
- Apply dimensional modeling and other data modeling techniques in a distributed data environment.
- Own the semantic layer within Databricks to support consistent definitions across reporting and analytics use cases.
- Enable downstream consumption by visualization and analytics tools, including Power BI, without relying on embedded semantic modeling.
- Partner with business analysts and reporting teams to improve dataset usability, performance, and scalability.
- Optimize datasets and data models for performance, including query efficiency and scalability for enterprise reporting workloads.
- Ensure data quality, integrity, and consistency across the full data lifecycle.
- Implement and enforce data governance standards, including data security, masking, access controls, and cost controls.
- Translate business requirements into scalable data solutions by working with business leaders and stakeholders.
- Align data structures to the enterprise data dictionary and KPI definitions.
- Communicate dataset structures and data model designs clearly to technical and non-technical stakeholders.
- Support the evolution of the enterprise analytics platform within Azure and Databricks.
- Contribute to CI/CD and deployment automation best practices, along with data engineering standards.
- Support advancement of data capabilities, including assistance with AI/ML use cases where applicable.
Required Qualifications
- Bachelor’s degree in Information Technology, Computer Science, Business Analytics, or a related field.
- 6+ years of experience in data engineering, data modeling, or analytics engineering roles.
- Strong expertise in Databricks Unity Catalog, SQL, and Python for data transformation and pipeline development.
- Proven experience designing and implementing data models within modern data platforms, including Lakehouse architecture.
- Experience working with medallion architecture (Bronze/Silver/Gold layers).
- Understanding of BI tools such as Power BI, with an emphasis on dataset consumption rather than semantic layer ownership.
- Experience with CI/CD pipelines, version control, and deployment processes.
- Familiarity with Agile/Scrum delivery methodologies.
Technology Stack
- Databricks, Databricks Lakehouse
- Databricks Unity Catalog
- SQL, Python
- Azure
- Power BI
- CI/CD pipelines
- Agile/Scrum
Compensation and Benefits
Salary: USD 135,000 - 155,000 per year.
Pay equity compensation range: USD 135,000 - 155,000.
- 401k with employer match
- Health/Dental/Vision insurance plans
- Paid time off
- 10 paid holidays
- Stock purchase plan
Location and Working Conditions
- Location: Texas (remote)
- Occasional travel may be required.
- Flexible work hours may be necessary to meet project deadlines.