Senior Data Engineer

Event Pipeline Ownership: Build and evolve the EventBridge → Firehose → S3 → Snowpipe ingestion path, including partitioning and throughput tuning as event volumes grow across streams like fraud, payments and merchant.

Batch & Third-Party Integrations: Design and deploy Snowpark-based Python procedures for file-based and third-party data loads, scheduled and monitored as Snowflake Tasks.

Schema Evolution: Work with product engineers to manage upstream schema changes and late-arriving data without breaking downstream consumers.

Infrastructure as Code: Own and extend Terraform/Terragrunt modules for ingestion infrastructure across multiple environments.

Pipeline Observability: Design Datadog monitors and alerting for Firehose, EventBridge, DLQs and Snowpipe; triage and resolve ingestion failures.

Security & Compliance: Manage PII handling (hashing, secure deletion), masking, data governance and access in Snowflake. Support audit-ready, reconciled data for Finance and Compliance.

Dbt: Build privacy-first data pipelines using dbt and Snowflake Dynamic Tables to safely expose sensitive data for downstream analytics and reporting.

Data Quality: Build testing and monitoring for ingestion and transformation logic to catch issues before they reach the business or the Analytics Engineering team.

Stakeholder Collaboration: Partner with the wider Engineering team and Analytics Engineering team as a downstream consumer, to ensure pipelines deliver accurate, audit-ready data.

AWS & Event-Driven Architecture: Hands-on experience with streaming/event ingestion (Kinesis, EventBridge or equivalents), S3 partitioning, and queue/DLQ patterns.

Infrastructure as Code: Terraform experience required; Terragrunt a plus. Comfortable owning modules across environments, not just consuming them.

Snowflake & Warehouse Engineering: Strong SQL for Snowflake, including Snowpipe, Tasks and Snowpark.

Dbt : Proven experience in building well tested SQL and python models in dbt.

CI/CD & Data Security: Experience with GitHub Actions (or equivalent), and secrets/key management, PII and sensitive data handling in Snowflake.

Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis.

Technical Communication: A pragmatic, systems-level mindset with the ability to explain pipeline failures, infrastructure trade-offs, or data-flow issues clearly to both engineers and non-technical stakeholders.

Ownership & Initiative : A strong willingness to work independently, take initiative, and take full ownership of the pipelines and infrastructure you build, from design and implementation through to production reliability.

Production Mindset : Proactively monitoring, debugging, and improving pipelines and infrastructure in production, not just building them and moving on.

*The stated experience and background is a guide and does not preclude applications from candidates with more or less experience, provided the requisite skills can be demonstrated.