{"id":1242980,"url":"https://alion.io/job/rbc-lead-data-engineer-2","title":"Lead Data Engineer","company":{"id":1757835,"name":"Royal Bank of Canada","domain":"rbc.com","url":"https://alion.io/company/rbc-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":85000,"max_usd":166000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"dbt","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Least Privilege","optional":false},{"name":"pySpark","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Hadoop","optional":true},{"name":"Kubernetes","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-09-16T00:00:00Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-09-28T22:57:15Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"Job Description\nWhat is the opportunity?\nAre you a hands-on data platform engineer who thrives on building cloud-native, high-scale data platforms and enabling teams on top of them? Come join us!\nGlobal Functions Technology (GFT) partners across RBC to deliver transformative platforms and solutions. In Anti-Money Laundering (AML), we are building a new Data Foundation Hub to ingest enterprise data and power analytics and controls using a medallion architecture. As a Lead Data Platform Engineer, you will be a senior individual contributor and technical lead, owning the design and build of our AWS-based data platform and mentoring other engineers.\nYou will work 70-80% hands-on across AWS (EKS, S3, RDS, EMR, Glue, Airflow), Snowflake, Spark, and dbt to deliver cloud-native, governed, and reliable data systems.\nWhat will you do?\nTechnical leadership and platform ownership\nLead the technical directionfor the AML Data Foundation Hub on AWS.\n\nMentor and coachengineers (techdesign reviews, pair programming, standards), influencing quality and delivery.\n\nCloud-native data platform on AWS (hands-on)\nDesign and build secure, scalable dataplatforms using AWS S3, Glue, EMR, RDS, and EKS.\n\nDefine patterns for data lake and warehouseintegration (e.g., S3 + Snowflake) including partitioning, storage classes,encryption, and cost optimization.\n\nImplement Infrastructure-as-Code (e.g., CloudFormation/Terraform) for repeatable environments, networking,IAM roles/policies, and security baselines.\n\nData engineering and architecture (medallion)\nDesign and build batch and incremental pipelinesacross Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark),Spark on EMR, and dbt.\n\nImplement schema evolution, SCD/CDC, partitioning, and performance tuning across bothcompute and storage (S3, EMR, Snowflake, RDS).\n\nIngestion, orchestration, and observability\nEngineer resilient, observable ingestion patterns intoS3/Snowflake/RDS.\n\nOrchestrate pipelines using Airflow (or equivalent) and/or AWS-native services (e.g., event triggers), enforcing SLAs, retries, idempotency, and alerting.\n\nBuild operational dashboardsand alerts for pipeline health, platform capacity, and cost.\n\nReliability, DR, and security\nDesign for high availability, resiliency, and disaster recovery (multi-AZ,/regionbackup/restore, RPO/RTO-aware architectures).\n\nImplement secrets management, encryption, IAM least-privilege, and network security inpartnership with Security and Platform/SRE.\n\nParticipate in incident response and postmortems; drive root-cause fixes and hardening ofthe platform.\n\nDevOps for data and platform enablement\nOwn CI/CD for data andplatform components: code review, environment promotion, automated tests (unit, integration, data contract), and versioned artifacts.\n\nPartner with Platform/SRE on SLIs/SLOs, capacity planning, and platform standardization across squads.\n\nCross-functional collaboration\nTranslate AML business and control objectives into technical roadmaps, platform capabilities, and reusable patterns.\n\nWhat do you need to succeed?\nMust-have\nExperience depth: 7+ years delivering production data pipelines and distributed systems at scale on cloud platforms; demonstrated ability to operate as a senior IC and technical lead influencing architecture and quality across a team.\n\nAWS platform depth: Hands-on with S3, Glue, EMR, EKS, and RDS; proficiency with IaC (CloudFormation or Terraform), IAM least-privilege design, VPC/networking, and security baselines.\n\nSnowflake expertise: Hands-on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization across compute and storage.\n\nDistributed processing: Production experience with Spark (PySpark/Scala) for large-scale batch processing, optimization, and tuning.\n\nData engineering and architecture: Medallion architecture patterns (Bronze/Silver/Gold), schema evolution, SCD/CDC, partitioning, and end-to-end pipeline performance tuning.\n\nOrchestration and automation: Airflow (or equivalent) for DAGs, SLAs, retries, idempotency, and observability; Git-based workflows and CI/CD for data pipelines (e.g., GitHub Actions/Jenkins).\n\nReliability and security: Designing for HA/DR (multi-AZ, backup/restore, RPO/RTO); encryption, secrets management, and network security in partnership with Platform/SRE.\n\nDevOps for data: Ownership of automated testing (unit, integration, data contract), environment promotion, and versioned artifacts.\n\nWays of working: Strong ownership, structured problem-solving, and clear technical communication; experience with incident response and postmortems.\n\nNice-to-have\ndbt proficiency: Development, testing, documentation, and deployment of transformations with dbt.\n\nObservability: Metrics, tracing, and logging practices across data pipelines and platform components.\n\nSecurity and privacy: OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services or AML.\n\nRegulated domains: Prior experience in financial services or other highly regulated industries.\n\nCloud depth: AWS certifications (e.g., Solutions Architect, Data Engineer) and hands-on familiarity with SageMaker or additional AWS-native data services.\n\nData governance: DQ frameworks, source-to-target reconciliation, lineage tooling, and purge/retention strategies.\n\nHadoop ecosystem: Exposure to legacy Hadoop stack where relevant to integration patterns.\n\nWhat's in it for you?\nAs a team, we thrive on the challenge to be our best, encourage progressive thinking for continued growth, and collaborate with one another to deliver trusted advice to help our clients thrive and our communities prosper. We respect and care about all of our team members and support one another in reaching our fullest potential. We work together to make a difference in our communities and to achieve success that is mutual.\nThis opportunity will provide you with:\nWork in a dynamic, collaborative, progressive, and high-performing team\n\nOpportunities to do challenging work, make a difference and lasting impact\n\nContinuous learning and flexibility to work on projects that you are passionate about\n\nLeaders who support your development through coaching and managing opportunities\n\n#LI-POST\n#TECHPJ\n Job Skills\nBig Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements AnalysisAdditional Job Details\nAddress:\nRBC CENTRE, 155 WELLINGTON ST W:TORONTOCity:\nTorontoCountry:\nCanadaWork hours/week:\n37.5Employment Type:\nFull timePlatform:\nTECHNOLOGY AND OPERATIONSJob Type:\nRegularPay Type:\nSalariedPosted Date:\n2026-08-06Application Deadline:\n2026-09-30Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above\nOur Employment Opportunities\nAt RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.\nJoin our Talent Community\nStay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.\nExpand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.\nRBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.","description_format":"text","description_chars":8137,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Wealth Management & Financial Advisors","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-09-25T16:58:10Z"}],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":1,"p_active":0.692,"p_room":0.35,"age_days":12,"expected_fill_days":6,"reasons":["conf:4","velocity","win:tail","comp:brand"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/rbc-lead-data-engineer-2","json_url":"https://alion.io/job/rbc-lead-data-engineer-2.json","meta":{"generated_at":"2026-09-29T03:50:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3656,"day_limit":5000,"remaining_today":1344,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}