At Netquest, we are looking for a Senior Data Engineer to join our team in Barcelona. We want someone eager to grow, learn, and make a real impact within a dynamic, collaborative, and tech-focused organization.
At Netquest, we are part of the most innovative and advanced digital data collection group in the market research and analytics industry. We rely on over 2.7 million consumers across 27 countries who share their opinions and behavioral data with us. Our ambition is to be the most reliable, flexible, and powerful data source on the market, shaping the future of market research through automation and innovation.
Our Data Team cover the three main pillars of the industry: Data Science, Data Analytics, and Data Engineering. Currently, we have met the existing needs in each area; now, we are transitioning from "making it work" to "making it infallible."
Your mission will be to actively contribute to and help define the gold standard for data reliability and observability within our ecosystem. Working closely with the Team Lead and the rest of the team, you will be a vital technical partner in elevating our engineering excellence.
Your Responsibilities
While we utilize a broad tech stack, we don’t expect you to be an expert in every single area listed below. We are looking for a solid foundation in data engineering and reliability, combined with the curiosity and ability to learn new technologies quickly as our ecosystem evolves.
Data Design Strategy & Architecture
- Ability to design, implement, and scale data pipelines from scratch, choosing between scale-up and scale-out approaches based on workload requirements.
- Deep understanding of data modeling, schema evolution, and the implementation of Data Governance principles across the organization.
- Mastery of best practices in design patterns for data transformation and a proven track record of implementing Idempotency, Data Lineage, and Reusability in complex environments.
Data Quality & Reliability (Our Key Focus)
- Experience creating and promoting Data Contracts and Quality Gates at every stage of the ETL/ELT process.
- Experience setting up SLIs/SLOs for data pipelines, automated alerting, and proactive incident management to ensure high data availability.
- Advanced focus on maintaining data health, monitoring intermediate data states, and ensuring integrity during reprocessing or backfilling.
- Deep understanding of unit, integration, and sanity testing specifically tailored for large-scale data processing and workloads.
Operational & Business Impact
- Ability to balance cost, performance, and maintenance when designing pipelines, focusing on long-term sustainability.
- Understanding how software changes or architectural shifts impact data delivery to both internal and external clients.