Design, develop, and maintain modern data solutions using Microsoft Fabric, including Lakehouse, Warehouse, Dataflows Gen2, Pipelines, Notebooks, and Semantic Models
Develop and optimize Power BI dashboards, reports, and analytical solutions, covering data modeling, DAX, visualization, and access management
Design, implement, and maintain scalable data transformation and modeling solutions using dbt
Develop centralized analytical data models based on Star and Snowflake schema principles
Explore and evaluate AI capabilities within Microsoft Fabric, identifying opportunities for automation, natural language querying, forecasting, and advanced data analysis
Requirements
Nice to have: railway or public transportation sector experience
Nice to have: 3+ years establishing and supporting data communities
Build, run, and own ETL pipelines on EMR (Spark) orchestrated in Airflow, write SQL and Python for data ingestion and transformation, own data quality, build and extend data models, work with analysts and stakeholders to deliver datasets.
Compensation
$100,000 -120,000
Responsibilities
Build, run, and own ETL pipelines on EMR (Spark) orchestrated in Airflow
Write SQL and Python for data ingestion, transformation, and the datasets that analysts and dashboards depend on
Own data quality for what you build
Build and extend the data models for your area
Keep your jobs efficient
Requirements
Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience
Design, develop, and maintain enterprise data platforms, data pipelines, and data warehouse solutions supporting healthcare analytics, reporting, and conversational AI applications.
Responsibilities
Design, develop, and maintain scalable ETL/ELT data pipelines.
Build cloud-based data engineering solutions using GCP and AWS.
Develop and maintain data models using Star and Snowflake schemas.
Design enterprise data warehouse architecture and data integration strategies.
Define and implement traditional and cloud-based ETL processes.
The Senior Data Engineer designs, builds, and maintains data pipelines, lakehouse models, and analytics data services for casino management systems using a modern Iceberg Data Lakehouse architecture.
Responsibilities
Design, build, and maintain components of the Iceberg Data Lakehouse using Apache Iceberg, Dremio, and Apache Polaris
Develop and maintain complex data pipelines using Python and Apache Kafka for efficient data ingestion, transformation, and storage
Build and maintain the curated data models and semantic layer in Dremio to power dashboards and self-service analytics
Build and maintain the data access layer that serves lakehouse data to downstream consumers
Implement integrations with diverse data sources through Kafka event streaming and Dremio query federation
Requirements
Bachelor’s or Master’s degree in Computer Science
Data Engineering
a related field
Nice to have: gaming or casino industry experience