Senior Engineer, Data Platform

Movable Ink•Toronto, ON

30d•$145,000 - $185,000

About The Position

Movable Ink scales content personalization for marketers through data-activated content generation and AI decisioning. The world’s most innovative brands rely on Movable Ink to maximize revenue, simplify workflow and boost marketing agility. Headquartered in New York City with close to 600 employees, Movable Ink serves its global client base with operations throughout North America, Central America, Europe, Australia, and Japan. As a Senior Engineer on the Data Platform team at Movable Ink, you will help design and build the systems that power how data flows through the organization. You will play a key role in developing and operating the unified data platform responsible for ingesting, processing, and exposing large volumes of data that drive Movable Ink’s products. Working closely with teammates across engineering, analytics, and infrastructure, you will build scalable ingestion pipelines and backend services that integrate data from a variety of sources while ensuring reliability, governance, and high availability across the platform. You will help evolve legacy pipelines toward modern data architectures, and help drive the unification of our products and services in how they access data. Your work will directly impact the growth and maturity of Movable Ink’s products and services.

Requirements

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
Proven ability to integrate systems, connecting legacy platforms with modern architectures through well-designed interfaces and migration strategies
Effective communicator who can facilitate system design discussions, document architectural decisions, and work across team boundaries
Experience designing and operating data systems on AWS; GCP experience is a plus
Strong collaboration and communication skills, comfortable leading design discussions, writing technical specs, and working across team boundaries
Experience with Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or similar

Nice To Haves

Familiarity with Elixir for building concurrent, fault-tolerant data services
Experience with data pipeline and streaming technologies such as Airflow, Kafka, Apache Flink, or similar
Hands-on experience with columnar/OLAP databases such as Databricks or ClickHouse

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

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