The Senior Data Engineer is a key member of the Data Engineering team, responsible for the Cloud Data Warehouse, Enterprise Data Warehouse and Data Lake. The successful candidate will be responsible for the delivery of project objectives and work on various Data Engineering initiatives, including activities such as: reviewing user stories, analysis of corporate data, and designing, developing, and testing Data Analytics and other data management solutions. The individual will be self-motivated and like do a variety of things, is a quick learner and is good with, and enjoys working with, data. A focus on delivery of high value solutions to the business should be a key driver and motivator.

5+ years' experience working in a directly comparable role responsible for cloud data warehouse and/or data lake development 2+ years' experience with Google Cloud Platform (BigQuery, GCS, Cloud Functions, Cloud Dataflow, Pub/Sub, Cloud Shell, GSUTIL, BQ command line utilities, DataProc, Cloud Operations) 2+ years' experience with other cloud data technologies such as AWS (S3, Glue, Lambda, Lake Formation, CloudFormation, Athena, Redshift) 5 years working directly with relational databases with strong SQL programming skills; experience with SQL Server (DBMS, SSAS Tabular Model, SSRS), including MDX and DAX 3 years' experience designing, building, and optimizing ‘big data’ pipelines, architectures and data sets 3 years' experience with modern programming languages (Python, PySpark, Java, etc.) Experience with big data solutions (Kafka, Hadoop, Spark, etc.), including data stream processing Experience designing a new data solution or new subject area Understanding of dimensional modeling, star schemas, and associated Kimball methodology Experience with data lakehouse and/or data mesh architectures a bonus Excellent verbal and written skills in English Exceptional attention to detail Experience working on an Agile development team Strong analytical, troubleshooting and problem-solving skills A proven ability to effectively prioritize and execute tasks in a high-pressure environment A strong work ethic without sacrificing your sense of humor or your ability to have fun on the job Occasional on-call availability. Occasional evening and weekend work to meet deadlines Professional office work environment/Typical Business office or home office work environment Work on building and architecting data pipelines for Data ingestion and transformation in Google Cloud Platform (GCP), AWS, and SQL Server Build, maintain, and monitor batch, micro-batch and real-time ETL/ELT pipelines in a Google Cloud Platform architecture (BigQuery, Cloud Composer, Cloud DataFlow, Google Cloud functions, etc.) Work closely with the Data Science and Analytics teams to develop a clear understanding of data and data infrastructure needs; assist with data-related technical issues Research and evaluate various approaches to data architecture and applications, including big data and cloud technologies; review existing artifacts and recommend solutions and technologies to implement Analyze corporate data, design and develop data analytics and other data management solutions Perform data validation and quality assurance Document requirements and business rules into appropriate technical specifications Participate in work planning and estimation Present technical solutions to various stakeholders Provide day-to-day support of the CDW, EDW and DL environments, with excellent customer service to internal clients, monitor new deployments and services, escalating issues where appropriate Create Tableau data sources and dashboards for various Business stakeholders Actively support the RB Unreserved Commitment to Safety: to send everyone home, every day, the way they came to work, by taking personal responsibility for your safety and safety of your team, co-workers and customers. Ensures team members follow processes and procedures set by the company and management. Flexible and willing to perform other tasks as assigned