Senior Data Engineer Iii

Data Engineer role involving data modeling, quality, acquisition, ETL, and metadata management. Responsibilities include data analysis, supporting data ingestion, creating data models and ETL jobs, and collaborating with technology teams.

Data Engineer role involving data modeling, quality, acquisition, ETL, and metadata management. Responsibilities include data analysis, supporting data ingestion, creating data models and ETL jobs, and collaborating with technology teams.

Data Engineer to implement data strategies by developing ETL pipelines, supporting dashboards for game/player insights, and collaborating with analytics teams. Requires SQL, Python, cloud databases, and orchestration tools.

Seeking a Data Engineer III to build and maintain scalable data pipelines and platforms using Python, Spark, AWS, and Snowflake for a leading QSR company. Role involves designing ETL/ELT, optimizing cloud-based data solutions, and collaborating with stakeholders.

Data Engineer to implement data strategies by developing ETL pipelines, supporting dashboards for game/player insights, and collaborating with analytics teams. Requires SQL, Python, cloud databases, and orchestration tools.

Seeking a Senior Data Engineer to build and scale a data platform for analytics, experimentation, and BI using Python, SQL, dbt, Airflow, and BigQuery/Snowflake. Requires collaboration with cross-functional teams and mentorship. Hybrid role in Toronto.

Seeking a Senior Data Engineer to build and maintain data lakehouse architecture and ETL/ELT pipelines. Responsibilities include technical leadership, code reviews, and solution design, with a focus on AWS, Snowflake, and data modeling.

Data Engineer responsible for developing data solutions, automating reporting pipelines, building real-time dashboards, and optimizing data queries using GCP technologies. Requires 5+ years of experience and strong SQL skills.

Seeking a Senior Data Engineer to design and implement scalable data architectures, optimize data pipelines, and build/maintain data models and lakes. Role focuses on transforming raw data into ML-ready features and ensuring data quality and reliability.