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Dremio

Open data lakehouse for in-place analytics

Senior Software Engineer

Backend EngineeringPosted on Nov 2
Full-timeRemote in PortugalNo salary listedRemote

About the Job

Requirements

  • Five or more years of professional software development experience, or equivalent practical experience.
  • Strong Java skills and experience with a substantial production codebase, supported by knowledge of data structures, algorithms, concurrency, API design, and distributed systems.
  • A record of owning backend or distributed-system features from design through rollout and production support, including estimating work and managing dependencies.
  • Ability to turn incomplete product requirements into implementation-ready specifications covering interfaces, invariants, failure cases, security, and acceptance criteria.
  • Experience directing AI coding agents, reviewing their plans and output, and correcting unsafe or unsuitable approaches; remain accountable for every owned change regardless of how the code was produced.
  • Strong code-review judgment, particularly around concurrency, authorization, compatibility, performance, and maintainability.
  • Experience validating changes through automated tests, static analysis, and production telemetry, then using that evidence to diagnose failures and address their root causes.
  • Clear written and verbal communication in specifications, design documents, technical discussions, and code reviews.
  • A bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Responsibilities

  • Own multiple features within the Catalog team, from requirements and technical design through implementation, testing, rollout, and production support.
  • Extend Apache Polaris while preserving compatibility with the Iceberg REST Catalog specification.
  • Build catalog APIs and services for namespaces, tables, views, identities, permissions, and metadata operations.
  • Solve distributed systems problems involving consistency, concurrency, failure recovery, multi-tenancy, and service performance.
  • Diagnose production issues using logs, metrics, traces, and service data, then address the underlying cause.
  • Write design documents for owned features and review designs from other engineers.
  • Work with query engine, security, platform, and product teams to define interfaces and manage dependencies.
  • Improve test coverage, operational tooling, and engineering practices in the areas owned.
  • Review code with attention to correctness, security, maintainability, and performance.
  • Share technical knowledge with the team and help onboard or mentor newer engineers.
  • Contribute fixes and features upstream when they belong in Apache Polaris or another open-source project.
  • Use AI-assisted development tools for code comprehension, debugging, and test generation, while verifying their output through engineering review and testing.

Desired Qualifications

  • Experience with Apache Polaris, Apache Iceberg, or the Iceberg REST Catalog specification.
  • Knowledge of metadata catalogs, authorization systems, credential vending, or policy enforcement.
  • Experience building multi-tenant cloud services.
  • Familiarity with databases, transaction isolation, and consistency models.
  • Experience with Kubernetes and public cloud infrastructure.
  • Familiarity with Apache Spark, Apache Flink, Trino, or other engines that integrate with Iceberg catalogs.
  • Contributions to Apache or other open-source projects.

About the Company

Dremio

Open data lakehouse for in-place analytics

Dremio provides an open data lakehouse platform that lets enterprises run self-service analytics directly on data lake storage without copying data into warehouses. It combines Dremio Sonar, a high-performance SQL query engine with an integrated semantic layer and Data Reflections for acceleration, with Dremio Arctic for Iceberg metadata management and Git-like branching to isolate work. It differentiates itself with in-place lake querying, an open-core model offering free and enterprise editions, and features for AI-assisted analytics through the Agentic Lakehouse. The goal is to help large organizations modernize their data infrastructure by enabling fast, self-service analytics with governance and AI-enabled insights.

Company size
201-500
Company stage
Series E
Total funding
$410M
Headquarters
Santa Clara, CA
Founded
2015

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