Rbc
DevOpsDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“DevOps Data Engineer at Rbc. Skills: DevOps, Data Engineering, Python, SQL, Cloud technologies, API Development, Microservices. Designs, develops, and optimizes data solutions. ensuring the delivery of high quality data assets, reporting, and business intelligence”
What You'll Achieve.
ensuring the delivery of high quality data assets, reporting, and business intelligence to support organizational objectives; making a difference and lasting impact; achieving success that is mutual
Industry & Context.
identify / foresee issues; proactively recommend and build resilient solutions; resolve data movement/transformation/processing bottlenecks; propose solutions
What They're Looking For.
Must Have
Bachelor’s degree in Computer Science, Engineering or equivalent, Experienced in building end to end data pipelines, Demonstrated leadership ability to identify / foresee issues and to proactively recommend and build resilient solutions, Advanced SQL knowledge and experience working with relational databases, Experience in developing scalable, configurable applications using Python and application frameworks, Knowledge of relevant security considerations for applications on cloud, Knowledge of VMs and various MLOps platforms such as WandB, AWS SageMaker, Knowledge of AWS, 5+ years of hands-on experience in following key areas: Data engineering solutions: Logstash, Python, SQL Server, Kafka, Hadoop, Spark, Trino; API: Streamlit, Flask, Node. JS, Django, and Microservices technologies; Automation/DevOps: Github Actions, Airflow, UCD, Selenium and similar technologies; Cloud technologies: Openshift, Docker, Kubernetes; Git & code version management
Nice to Have
Security frameworks: LDAP, Kerberos, OAuth 2. 0, Vault integration, Visualization tools: Dash, Plotly, Tableau, Experience working in agile environment, Master’s degree in Computer Science, Engineering, or equivalent, Supervised and Unsupervised Machine learning, Natural Language Processing
What You'll Do.
and optimizes data solutions
ensuring the delivery of high quality data assets
and business intelligence
Manages data engineering projects or assignments of increasing complexity
encompass an end to end view from data sourcing
transformation and storage
Execute Development and Integration activities (planning
deployment and post implementation support) of existing and new data and visualization Technologies
Prepare data to be used for diagnostic/descriptive reporting and data science work
Build container based solutions
APIs/Microservices and analytics portal for heterogeneous data sources on internal data lakes or cloud platforms
Identify and resolve data movement/transformation/processing bottlenecks
Research emerging Data and Visualization technologies trendsest practices and propose solutions for Technology and Business partners
How You'll Work.
Team & Collaboration
Collaborate with Data scientists, Process Engineers and Business Stakeholders to develop data pipelines; working together to deliver trusted advice; working together as One RBC; effectively collaborate; dynamic, collaborative, progressive, and high-performing team
Communication Scope
deliver trusted advice
Process & Methodology
Manages data engineering projects or assignments of increasing complexity, scope and impact, planning, execution
Full Job Description
**_Job Description_** **What is the opportunity?** Designs, develops, and optimizes data solutions, ensuring the delivery of high quality data assets, reporting, and business intelligence to support organizational objectives. Manages data engineering projects or assignments of increasing complexity, scope and impact, applying professional judgment and expertise. **What will you do?** * As part of the Data Engineering team, you will encompass an end to end view from data sourcing, lineage, quality, transformation and storage. * Execute Development and Integration activities (planning, execution, testing, deployment and post implementation support) of existing and new data and visualization Technologies (e.g. streamlit). * Prepare data to be used for diagnostic/descriptive reporting and data science work. * Build container based solutions, pipelines, APIs/Microservices and analytics portal for heterogeneous data sources on internal data lakes or cloud platforms * Collaborate with Data scientists, Process Engineers and Business Stakeholders to develop data pipelines, and assist with prescriptive and predictive analytics through consolidated data * Identify and resolve data movement/transformation/processing bottlenecks * Research emerging Data and Visualization technologies trends/best practices and propose solutions for Technology and Business partners. **What do you need to succeed?** **Must Have:** * Bachelor’s degree in Computer Science, Engineering or equivalent * Experienced in building end to end data pipelines * Demonstrated leadership skills; ability to identify / foresee issues and to proactively recommend and build resilient solutions * Advanced SQL knowledge and experience working with relational databases * Experience in developing scalable, configurable applications using Python and application frameworks * Knowledge of relevant security considerations for applications on cloud * Knowledge of VMs and various MLOps platforms such as WandB, AWS SageMaker *
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