Software Engineer, Data Platform

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and implement data ingestion pipelines and infrastructure.

• Transition legacy data lifecycle management to the new platform while ensuring minimal disruption to existing data consumers.

• Establish and uphold Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with dashboards and alerts to monitor platform performance.

• Develop adaptable data storage solutions that support transactional, analytical, and machine learning workloads.

• Execute monitoring, observability, and incident response for event data pipelines and related services.

• Collaborate with product engineering, analytics, and machine learning teams to outline contracts, requirements, and standards.

• Create and implement a semantic metadata layer for data classification, discovery, exposure policies, and cross-product reuse.

• Architect and deliver a secure, multi-tenant data model that facilitates client data sharing and maintains isolation.

• Report to the Engineering Manager of the Data Platform.

⛳️ Requirements

• Willingness to learn new technologies, frameworks, and problem domains.

• A product- and end-user-focused mindset for addressing broad challenges.

• In-depth knowledge of data governance and data lifecycle management, including aspects such as quality, lineage, retention, and access control.

• Production-level experience with OLAP/OLTP databases and data warehouses, including Databricks, ClickHouse, or Redshift.

• Proficient SQL skills, encompassing query writing and optimization.

• Experience in designing and managing data systems on AWS; experience with GCP is an advantage.

• Familiarity with multi-cloud deployment environments.

• Proficiency in Docker and Kubernetes.

• Capability to integrate legacy platforms with modern architectures through interfaces and migration strategies.

• Ability to lead system design discussions and document architectural decisions.

• Knowledge of Elixir for concurrent, fault-tolerant data services (preferred).

• Experience with Airflow, Kafka, Apache Flink, or other similar streaming technologies (preferred).

• Hands-on experience with columnar/OLAP databases such as Databricks or ClickHouse (preferred).

• Familiarity with Infrastructure-as-Code tools like Terraform or CloudFormation.

• Strong collaboration and communication abilities; comfortable leading design discussions and producing technical specifications.

🏝️ Benefits

• Additional bonus based on the specific position offered.

• Comprehensive medical, financial, and/or other benefits.