2 months ago
Remote, WorldwideSenior
Responsibilities
- Design and build scalable data engineering services for analytics, reporting, machine learning, and AI workloads.
- Build and maintain reliable CDC- and event-driven data ingestion pipelines.
- Develop and evolve a centralized analytics warehouse for performance, scalability, and maintainability.
- Design data models, materialized views, and aggregation strategies for product analytics and business reporting.
- Build APIs and backend services exposing analytics and reporting capabilities to internal and external consumers.
- Implement multi-tenant security controls, data governance standards, and access management policies.
- Monitor pipeline health, data freshness, ingestion lag, and overall system reliability.
- Contribute to technical specifications, architecture discussions, and system design decisions.
- Improve developer productivity through automation, tooling, observability, and operational excellence.
- Strengthen test coverage and engineering practices and participate in on-call rotations.
Requirements
- At least 5 years of hands-on software engineering experience building and operating scalable distributed systems, data engineering solutions, or backend services in production.
- Mandatory hands-on experience building and maintaining production-grade backend services.
- Experience with system design, backend systems, product-based environments, and technical or architectural decision-making.
- Strong experience with analytical data warehouses such as ClickHouse, BigQuery, Snowflake, or Amazon Redshift; deep ClickHouse expertise is a plus.
- Experience designing and operating large-scale ingestion pipelines using Kafka, Pulsar, CDC architectures, or related streaming technologies.
- Familiarity with Debezium, Flink, Dataflow, or similar streaming and data processing frameworks is preferred.
- Strong SQL skills, including data modeling, query optimization, and analytical workloads.
- Experience with large-scale data processing and transformation workloads in data engineering or analytics engineering.
- Experience building backend services in Go or another modern strongly typed language, plus proficiency in Python.
- Experience with cloud platforms, preferably GCP, including managed data, messaging, and observability services.
- Experience owning production systems end to end across technical design, stakeholder discussions, deployment, operational support, and iterative improvement.
- Experience with multi-tenant SaaS platforms, data governance, data security controls, and infrastructure-as-code tools such as Terraform.
- Experience with PostgreSQL, TimescaleDB, or similar analytical and time-series databases.
- Exposure to AI-powered applications, LLM integrations, or agentic workflows is an advantage.
- Strong problem-solving, communication, collaboration, proactive ownership, and ability to work with technical and non-technical stakeholders.
Tech Stack
Amazon RedshiftApache FlinkApache KafkaClickHouseGoGoogle BigQueryGoogle Cloud PlatformPostgreSQLPythonSnowflakeSQLTerraform
Categories
BackendData Engineering
About Maropost
Maropost builds a unified commerce platform for ecommerce merchants and retailers, combining online storefronts, merchandising, marketing automation, customer service, and payments in one SaaS suite. Founded in 2011 and headquartered in Toronto, it is privately held and serves thousands of brands, including Mercedes‑Benz, Seiko, and Fujifilm. The company has been recognized on Deloitte’s Technology Fast 500 and G2 category lists.