Lead Data Engineer

<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p style="text-align:left"><b><u>Job Description</u></b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><p><b>What is the opportunity?

</b></p><p></p><p>Are 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!</p><p></p><p>Global 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.</p><p></p><p>You 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.</p><p></p><p><b><span>What will you do?

</span></b></p><ul><li><p><b>Technical leadership and platform ownership</b></p><ul><li><p><span>Lead the technical direction</span><span> for the AML Data Foundation Hub on AWS.</span></p></li><li><p><span>Mentor and coach</span><span> engineers (tech</span><span> design reviews, pair programming, standards</span><span>), influencing quality and delivery</span><span>.</span></p></li></ul></li><li><p><b>Cloud-native data platform on AWS (hands-on)</b></p><ul><li><p><span>Design and build secure, scalable data</span><span> platforms using </span><b>AWS S3, Glue, EMR, RDS, and EKS</b><span>.

</span></p></li><li><p><span>Define patterns for data lake and warehouse</span><span> integration (e.g., S3 + Snowflake</span><span>) including partitioning, storage classes,</span><span> encryption, and cost optimization.</span></p></li><li><p><span>Implement </span><b>Infrastructure-as-Code</b><span> (e.g., CloudFormation/Terraform</span><span>) for repeatable environments</span><span>, networking,</span><span> IAM roles/policies</span><span>, and security baselines.

</span></p></li></ul></li><li><p><b>Data engineering and architecture (medallion)</b></p><ul><li><p><span>Design and build batch and incremental pipelines</span><span> across </span><b>Bronze/Silver/Gold</b><span> layers using</span><span> </span><b>Snowflake (Streams, Tasks, Snowpark)</b><span>,</span><span> </span><b>Spark on EMR</b><span>, and </span><b>dbt</b><span>.</span></p></li><li><p><span>Implement </span><b>schema evolution, SCD/CDC, partitioning, and performance tuning</b><span> across both</span><span> compute and storage (S3, EMR, Snowflake</span><span>, RDS).

</span></p></li></ul></li><li><p><b>Ingestion, orchestration, and observability</b></p><ul><li><p><span>Engineer resilient, observable ingestion patterns </span><span>into</span><span> S3/Snowflake/RDS.</span></p></li><li><p><span>Or</span><span>chestrate pipelines using </span><b>Airflow</b><span> (or equivalent</span><span>) and/or AWS</span><span>-native services (e.g., event triggers), enforcing </span><b>SLAs, retries, idempotency, and alerting</b><span>.

</span></p></li><li><p><span>Build operational dashboards</span><span> and alerts for pipeline health, platform capacity</span><span>, and cost.</span></p></li></ul></li><li><p><b>Reliability, DR, and security</b></p><ul><li><p><span>Design for </span><b>high availability, resiliency, and disaster recovery</b><span> (multi-AZ,/region</span><span> backup/restore, RPO/RTO-aware architectures).

</span></p></li><li><p><span>Implement </span><b>secrets management, encryption, IAM least-privilege</b><span>, and network security in</span><span> partnership with Security and Platform/SRE.</span></p></li><li><p><span>Participate in incident response and postmortems; drive root-c</span><span>ause fixes and hardening of</span><span> the platform.</span></p></li></ul></li><li><p><b>DevOps for data and platform enablement</b></p><ul><li><p><span>Own CI/CD for data and</span><span> platform components: code review, environment promotion, automated tests (</span><span>unit, integration, data contract), and versioned artifacts.

</span></p></li><li><p><span>Partner with Platform/SRE on </span><b>SLIs/SLOs, capacity planning</b><span>, and platform standard</span><span>ization across squads.</span></p></li></ul></li><li><p><b>Cross-functional collaboration</b></p><ul><li><p><span>Translate AML business and control objectives into </span><b>technical roadmaps, platform capabilities, and reusable patterns</b><span>.

</span></p></li></ul></li></ul><p></p><p></p><p><b><span>What do you need to succeed?</span></b></p><p></p><p><b><span>Must-have</span></b></p><ul><li><p><b><span>Experience depth:</span></b><span> 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.

</span></p></li><li><p><b><span>AWS platform depth:</span></b><span> Hands-on with S3, Glue, EMR, EKS, and RDS; proficiency with IaC (CloudFormation or Terraform), IAM least-privilege design, VPC/networking, and security baselines.</span></p></li><li><p><b><span>Snowflake expertise:</span></b><span> Hands-on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization across compute and storage.

</span></p></li><li><p><b><span>Distributed processing:</span></b><span> Production experience with Spark (PySpark/Scala) for large-scale batch processing, optimization, and tuning.</span></p></li><li><p><b><span>Data engineering and architecture:</sp