greenhouse
Senior Engineer, Data Platform
Movable Ink
Toronto, CAN
Full-time
Senior
Onsite
USD 145000-185000 yearly / year
Discovered 3 weeks ago
DatabricksClickHouseRedshiftSQLAWSGCP
Free
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DatabricksClickHouseRedshift
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DatabricksClickHouseRedshiftSQLAWSGCP
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Responsibilities
- Support the design and delivery of data ingestion pipeline and infrastructure
- Assist in the successful migration of legacy data lifecycle management to new platform without disrupting existing data consumers
- Establish and maintain SLIs and SLOs for new ingestion and data platform with dashboards and alerting to track performance
- Build flexible data storage layer supporting a variety of use cases, e.g., transactional, analytic, and machine learning workloads
- Implement comprehensive monitoring, observability, and incident response practices for all event data pipelines and services
- Collaborate with product engineering, analytics, and machine learning teams to define contracts, functional requirements, and standards
- Design and implement a semantic metadata layer that classifies and labels data assets across both products, enabling consistent data discovery, exposure policies, and identification of cross-product data reuse opportunities
- Architect and deliver a multi-tenant data model that supports secure data sharing and isolation across clients, with controls designed to meet regulatory and government compliance requirements
Qualifications
- Deep understanding of data governance principles and data lifecycle management, including data quality, lineage, retention, and access control
- Strong familiarity with database backend technologies (OLAP vs. OLTP) and when to apply each, with hands-on experience using data warehouse technologies (Databricks, Clickhouse, Redshift, etc) at production scale
- Strong familiarity with SQL with the ability to write and optimize queries
- Skill at building complex systems and identifying core primitives and how to apply them to meet changing business needs and future roadmap requirements.
- Experience designing and operating data systems on a major cloud provider (AWS or GCP) and working in a multi-cloud deployment environment
- Proficiency with containerization and orchestration technologies, including Docker and Kubernetes
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