Senior Software Engineer, Data Engineer
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Job Description
Senior Software Engineer (Data Engineer) developing scalable data solutions for analytics and AI at Maropost. Collaborating across teams to deliver end-to-end engineering solutions with minimal dependencies.
Responsibilities:
- Design and build scalable data engineer services that power analytics, reporting, machine learning, and AI workloads across Maropost products.
- Build and maintain reliable data ingestion pipelines using CDC and event-driven architectures.
- Develop and evolve our centralized analytics warehouse, ensuring high performance, scalability, and maintainability.
- Design and implement data models, materialized views, and aggregation strategies to support product analytics and business reporting.
- Build supporting APIs and services that expose analytics and reporting capabilities to internal and external consumers.
- Define and implement multi-tenant security controls, data governance standards, and access management policies.
- Monitor data pipeline health, data freshness, ingestion lag, and overall system reliability.
- Contribute to technical specifications and actively participate in architecture and design discussions.
- Improve developer productivity through automation, tooling, observability, and operational excellence.
- Strengthen test coverage and engineering practices to ensure reliable and maintainable systems.
Requirements:
- 5+ years of hands-on software engineering experience building and operating highly scalable distributed systems, data engineering solutions, or backend services in production.
- Strong experience with modern analytical data warehouses such as ClickHouse, BigQuery, Snowflake, or Amazon Redshift.
- Deep expertise in ClickHouse, including internals, materialized views, and OLAP workload optimization, is a plus.
- Experience designing and operating large-scale data ingestion pipelines using Kafka, Pulsar, CDC-based architectures, and related streaming technologies.
- Familiarity with tools such as Debezium, Flink, Dataflow, or similar streaming and data processing frameworks is preferred.
- Strong SQL skills with hands-on experience in data modelling, query optimization, and analytical workloads.
- Experience working on data engineering, or analytics engineering initiatives involving large-scale data processing and transformation workloads.
- Experience building and maintaining backend services in Go (preferred) or another modern strongly typed programming language, along with proficiency in Python.
- Experience with cloud platforms, preferably GCP, including managed data, messaging, and observability services.
- Experience owning and delivering production systems end-to-end, from technical design and stakeholder discussions through deployment, operational support, and iterative improvements across multiple release cycles.
- Experience with multi-tenant SaaS platforms, data governance practices, data security controls, and infrastructure-as-code tools such as Terraform.
- Experience with analytical and time-series databases such as PostgreSQL, TimescaleDB, or similar technologies.
- Exposure to AI-powered applications, LLM integrations, or agentic workflows is an added advantage.
- Comfortable participating in on-call rotations and focused on building simple, efficient solutions without over-engineering.
- Proactive and self-driven, with strong problem-solving and communication skills, and the ability to collaborate effectively with both technical and non-technical stakeholders.
Benefits:
- Flexible work arrangements
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