Staff Software Engineer - Curated Data

Jobgether; España; A distancia; PHP 7.231.000 - 10.846.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary and equity package

Employee equity plan with discounted 8

5 weeks of paid time off

Fully remote-first environment

Flexible working hours

Asynchronous collaboration

Private medical, dental, and vision

Parental leave

Annual travel allowance

Home-office setup allowance

Descripción de la vacante

Jobgether is seeking a Staff Software Engineer - Curated Data for a partner company, fully remote. You will design systems powering high-quality, trusted datasets in a distributed, onchain data environment.

Expect responsibility for data orchestration, schema evolution, and reliable software contracts across multiple languages. You will own architecture decisions, propagate schema changes, and build scalable components while maintaining strong engineering standards with asynchronous

Formación

• Significant backend experience with data systems.

Responsabilidades

• Design and build the control plane for curated data lifecycle.

Conocimientos

Backend engineering

Data systems

Distributed systems

SQL

Go

Kotlin

Rust

Python

Architectural thinking

Asynchronous collaboration

AI tooling

Data modeling

Herramientas

Flink

Kafka Streams

Spark

RisingWave

Materialize

Feldera

dbt

SQLMesh

Parquet

Iceberg

Delta Lake

Descripción del empleo

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer - Curated Data based in Spain.

As a Staff Software Engineer, you will help design the systems that power high-quality, trusted datasets across a rapidly evolving onchain data environment.
You will own challenging problems around data orchestration, dependency management, schema evolution, corrections, and recovery at significant scale.
The role combines deep backend engineering with data systems expertise, requiring strong architectural thinking and a focus on reliable software contracts.
You will take ambiguous product requirements, turn them into clear technical designs and execution plans, and personally build the most complex components.
Working across multiple programming languages and technologies, you will choose the right solution based on the problem rather than familiarity.
You will also help distributed engineering teams break down complex initiatives, ship incrementally, and maintain high engineering standards.
This is an opportunity to have substantial technical influence while working on foundational systems where data quality and correctness are critical.

Accountabilities

• Design and build the control plane for the curated data lifecycle, including dependency-aware orchestration, backfills, restatements, retries, partial-failure handling, and recovery mechanisms.

• Own architectural decisions across datasets, determining when a problem is best addressed through a data model, service, or job.

• Design and maintain clear contracts between data ingestion and curation layers so datasets can be understood and managed end to end.

• Build reliable alerting, monitoring, and data-quality signals that identify genuine issues while minimising operational noise.

• Work across Go, Kotlin, Rust, Python, and SQL, selecting technologies based on the requirements of each problem.

• Develop software that orchestrates and manages thousands of interdependent data models and supports large-scale data operations.

• Design systems capable of propagating schema changes and data corrections without unnecessarily disrupting downstream consumers.

• Translate ambiguous product requirements into technical designs, execution sequences, and actionable work for the broader engineering team.

• Personally implement the most technically challenging components while enabling other engineers to own and deliver complementary work.

• Debug complex production issues independently and lead root-cause analysis through to durable fixes.

• Contribute to technical architecture, engineering practices, and system design decisions across the curated data domain.

• Collaborate effectively with a distributed engineering organisation through clear written communication and a strong async-working approach.

• Use AI-assisted development tools thoughtfully to increase engineering productivity while validating outputs and maintaining high standards for correctness and quality.

Requirements

• Significant experience as a backend software engineer with deep expertise in data systems, or as a data engineer who has developed strong software engineering capabilities.

• Proven track record of building and operating production-grade services, not solely data pipelines.

• Experience designing, building, or materially extending orchestration and scheduling systems, with a strong understanding of their failure modes and scaling challenges.

• Demonstrated experience with schema evolution and data correctness in systems where downstream consumers depend on reliable and stable data.

• Production experience with stateful stream-processing technologies such as Flink, Kafka Streams, Spark Structured Streaming, RisingWave, Materialize, or Feldera.

• Strong SQL and data-modelling capabilities, particularly when working with large datasets.

• Solid computer science fundamentals and a strong understanding of distributed systems.

• Experience reasoning about query execution and the underlying behaviour of data-processing engines is highly valuable.

• Strong debugging and root-cause-analysis skills, with a track record of driving issues through to durable production fixes.

• Strong architectural and systems-thinking abilities, with the confidence to make decisions across complex technical domains.

• Ability to take ambiguous requirements, develop a clear design and implementation sequence, and turn large technical problems into manageable workstreams.

• Strong written communication skills and the ability to collaborate effectively within distributed engineering teams.

• Practical experience using AI development tools and an understanding of their limitations, failure modes, and appropriate use in production engineering workflows.

• Experience with transformation frameworks such as dbt or SQLMesh is a plus, particularly experience extending them after encountering their limitations.

• Familiarity with data-lake formats such as Parquet, Iceberg, or Delta Lake is advantageous.

• Experience working in an organisation where data itself is a core product is a plus.

Benefits

• Competitive salary and equity package, positioned within the top 25% of companies in the sector.

• Employee equity plan with employee-friendly terms, including a heavily discounted strike price and a 10-year exercise window.

• 5 weeks of paid time off plus local public holidays, with flexibility to swap holidays where appropriate.

• Fully remote-first working environment within a distributed international team.

• Flexible working hours, allowing you to structure your working day around your productivity and priorities.

• Strong focus on asynchronous collaboration and a deliberate approach to reducing unnecessary meetings.

• Private medical, dental, and vision insurance.

• 16 weeks of fully paid parental leave for primary caregivers and 6 weeks for secondary caregivers.

• Two-week phased return to work at full pay following parental leave.

• Quarterly company or team offsites at international locations.

• Annual travel allowance for connecting and co-working with colleagues.

• Home-office setup allowance, with local coworking space costs covered if preferred.

• Opportunity to work alongside experienced engineers and specialists in a highly collaborative environment.

• Company merchandise and team perks.