Senior Manager, Engineering & Build

What will you do?

• People leadership and team performance:
  Lead, mentor, and grow a high‑performing team; drive delivery excellence, coaching, goal setting, and continuous improvement.
• Hands‑on data engineering and system design (≈50%):
  Design and build batch and incremental pipelines across Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark, Snowpipes), Spark, and dbt; implement schema evolution, SCD/CDC, partitioning, and performance tuning.
• Cloud‑native solution design:
  Architect for reliability, scalability, and cost efficiency on cloud platforms; containerize jobs/services, run on Kubernetes/Open Shift, apply IaC, and secure secrets and credentials.
• Dev Ops for data and platform enablement:
  Own CI/CD for data (code review, environment promotion, data contract testing), versioned artifacts, and environment parity; partner with Platform/SRE on SLIs/SLOs, incident response, and postmortems.
• Data Platform:
  Engineer resilient, observable ingestion patterns (batch first, with optional near‑real‑time), orchestrate with Airflow, enforce SLAs, retries, idempotency, and alerting; establish DQ controls, source‑to‑target reconciliation, and end‑to‑end lineage; implement purge/retention aligned to AML and regulatory requirements.
• Cross‑functional collaboration:
  Translate AML business and control objectives into technical roadmaps; collaborate with Business, Data Governance, Compliance, Security, and Operations; identify and mitigate risks; champion innovation.

• 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.
• Snowflake expertise: Hands‑on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization.
• Distributed processing: Production experience with Spark (PySpark/Scala) for large‑scale batch processing and optimization.
• Modeling and architecture: Strong data modeling (3NF/dimensional/data vault) and medallion architecture patterns.
• Data governance controls: Data quality frameworks, source‑to‑target reconciliation, lineage concepts and tooling, purge/retention strategies.
• Orchestration and automation: Airflow (or equivalent) for DAGs, SLAs, retries, and observability;
  Git‑based workflows and CI/CD for data.
• Dbt proficiency: Development, testing, documentation, and deployment of transformations with dbt.
• Cloud‑native and platform: Containers, Kubernetes/Open Shift, IaC, and secure secret management; understanding of cost/performance trade‑offs.
• Ways of working: Strong ownership, excellent problem solving and communication; incident management and postmortems.
• Technology focus: Snowflake, Spark, dbt, Airflow, Python/Scala/Java, Open Shift/Kubernetes, public cloud (e.g., AWS).

• Streaming and events: Kafka/CDC for near‑real‑time enrichment into batch layers.
• Observability: Metrics, tracing, and logging practices and tooling across data pipelines.
• Security and privacy: OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness.
• Regulated domains: Experience in financial services or other highly regulated industries.
• Cloud depth: Certifications (AWS) and familiarity with services such as Glue, EMR, EKS, Sage Maker.
• Stakeholder management: Ability to influence and align diverse technical and non‑technical partners.
• Hadoop ecosystem exposure where applicable.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
• Leaders who support your development through coaching and managing opportunities.
• Work in a dynamic, collaborative, progressive, and high‑performing team.
• A world‑class training program in financial services.
• Flexible work/life balance options.
• Opportunities to take on progressively greater accountabilities.
• Access to a variety of job opportunities across business and geographies.