Senior Manager, Engineer & Build

<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><span style="color:#000000"><span style="font-size:inherit"><br /></span></span><b>What is the opportunity?

<br /></b></p><p><span style="font-size:inherit">Are you a hands-on data engineering leader who thrives on building high-performing teams and high-scale data platforms? Come join us!</span></p><p><span style="font-size:inherit">Global Functions Technology (GFT) partners across RBC to deliver transformative platforms and solutions. In Anti-Money Laundering (AML), we are building a Data Foundation Hub to ingest enterprise data and power analytics and controls using a medallion architecture.

</span></p><br /><p><span style="font-size:inherit">As a Senior Manager, Engineering & Build (Hands-On Leader), you will lead an engineering team while contributing ≈50% hands-on to design and deliver cloud-native, governed, and reliable data systems.</span></p><br /><p><b><span style="font-size:inherit">What will you do?</span></b></p><br /><ul><li><span style="font-size:inherit">Lead, mentor, and grow a high-performing team; drive delivery excellence, coaching, goal setting, and continuous improvement.

</span></li><li><span style="font-size:inherit">Design and build batch and incremental pipelines across Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark, Snowpipes), Spark, and dbt.</span></li><li><span style="font-size:inherit">Implement schema evolution, SCD/CDC, partitioning, and performance tuning.</span></li><li><span style="font-size:inherit">Architect for reliability, scalability, and cost efficiency on cloud platforms.

</span></li><li><span style="font-size:inherit">Containerize jobs/services, run on Kubernetes/OpenShift, apply IaC, and secure secrets and credentials.</span></li><li><span style="font-size:inherit">Own CI/CD for data (code review, environment promotion, data contract testing), versioned artifacts, and environment parity.</span></li><li><span style="font-size:inherit">Partner with Platform/SRE on SLIs/SLOs, incident response, and postmortems.

</span></li><li><span style="font-size:inherit">Engineer resilient, observable ingestion patterns (batch first, with optional near-real-time).</span></li><li><span style="font-size:inherit">Orchestrate with Airflow (or equivalent); enforce SLAs, retries, idempotency, and alerting.</span></li><li><span style="font-size:inherit">Establish DQ controls (profiling, constraints, dbt tests), source-to-target reconciliation, and end-to-end lineage.

</span></li><li><span style="font-size:inherit">Implement purge/retention aligned to AML and regulatory requirements.</span></li></ul><p><br /><b><br /></b></p><p><b><span style="font-size:inherit">What do you need to succeed?</span></b></p><p><b><span style="font-size:inherit">Must-have:</span></b></p><ul><li><span style="font-size:inherit">Experience depth: 10+ years in engineering delivering production pipelines and distributed systems at scale; 2–4+ years leading engineers with a proven balance of hands-on and people leadership.

</span></li><li><span style="font-size:inherit">Snowflake expertise: Hands-on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization.</span></li><li><span style="font-size:inherit">Distributed processing: Production experience with Spark (PySpark/Scala) for large-scale batch processing and optimization.</span></li><li><span style="font-size:inherit">Modeling and architecture: Strong data modeling (3NF/dimensional/data vault) and medallion architecture patterns (Bronze/Silver/Gold).

</span></li><li><span style="font-size:inherit">Data governance controls: Data quality frameworks, source-to-target reconciliation, lineage concepts and tooling, purge/retention strategies.</span></li><li><span style="font-size:inherit">Orchestration and automation: Airflow (or equivalent) for DAGs, SLAs, retries, and observability; Git-based workflows and CI/CD for data (e.g., GitHub Actions/Jenkins).

</span></li><li><span style="font-size:inherit">Dbt proficiency: Development, testing, documentation, and deployment of transformations with dbt.</span></li><li><span style="font-size:inherit">Cloud-native and platform: Containers, Kubernetes/OpenShift, Infrastructure-as-Code, and secure secret management; understanding of cost/performance trade-offs.</span></li><li><span style="font-size:inherit">Ways of working: Strong ownership, and excellent problem solving and communication; incident management and postmortems.

</span></li><li><span style="font-size:inherit">Technology focus: Snowflake, Spark, dbt, Airflow, Python/Scala/Java, OpenShift/Kubernetes, and public cloud (e.g., AWS).</span></li></ul><br /><p><b><span style="font-size:inherit">Nice-to-have:</span></b></p><ul><li><span style="font-size:inherit">Streaming and events: Kafka/CDC for near-real-time enrichment into batch layers.</span></li><li><span style="font-size:inherit">Observability: Metrics, tracing, and logging practices and tooling across data pipelines.

</span></li><li><span style="font-size:inherit">Security and privacy: OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services/AML.</span></li><li><span style="font-size:inherit">Regulated domains: Experience in financial services or other highly regulated industries.</span></li><li><span style="font-size:inherit">Cloud depth: Certifications (AWS) and familiarity with services such as Glue, EMR, EKS, SageMaker.

</span></li><li><span style="font-size:inherit">Stakeholder management: Ability to influence and align diverse t