Data Engineer
Barcelona · Barcelona, Spain
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
R&D › Engineering — team source
Department: R&D › Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you require visa sponsorship or a visa transfer?
From the employer’s application form
What you’ll work on
Full postingLead improvements to data architecture using Data Mesh principles
Develop, scale and maintain the cloud data platform infrastructure
Lead data lineage and governance practices across the organisation
Build custom ETL pipelines, detect anomalies and create optimised aggregations
Support the Product and Engineering organisation with its data needs
From the employer’s posting
Take a leading role in the improvement of our Data architecture by applying Data Mesh principles.
Develop, scale, maintain and deploy our data platform infrastructure in the cloud.
Take a leading role in applying Data Lineage and Governance throughout the organisation.
Develop custom ETL pipelines, detect anomalies, and create optimised aggregations for analysis and dash boarding.
Support the entire Product & Engineering organisation in their data needs.
What you’ll bring
All qualificationsCore experience
- 5+ years of data engineering experience
- Experience designing data platforms and making architectural decisions
- Hands-on work with Spark and Kafka data pipelining tools
- Experience with AWS data services such as S3, Glue, Athena and EMR
- Experience with Airflow, Snowflake and Terraform
Qualification wording
Minimum of 5+ years of Data Engineering experience
Designing Data Platforms and taking architectural decisions, leading the way towards better data ecosystems.
Using industry standard data pipelining tools (Spark, Kafka).
Working with AWS (S3, Glue, Athena, EMR, etc.).
Using data/task orchestration tools (Airflow).
Tools in this posting
- AWS
- Kafka
- S3
- Snowflake
- Spark
- Terraform
- Airflow
Source — Tool mentions in context
- Using industry standard data pipelining tools (Spark, Kafka). - Working with AWS (S3, Glue, Athena, EMR, etc.). - Using data/task orchestration tools (Airflow).
- Developing data flows for the processing of data at scale. - Using industry standard data pipelining tools (Spark, Kafka). - Working with AWS (S3, Glue, Athena, EMR, etc.).
- Using data/task orchestration tools (Airflow). - Cloud computing-based data cloud solutions (Snowflake). - Using infrastructure-as-code solutions (Terraform).
- Cloud computing-based data cloud solutions (Snowflake). - Using infrastructure-as-code solutions (Terraform). - Partnering with cross-functional teams of engineers, data scientists and devops in defining a modern data architecture.
- Working with AWS (S3, Glue, Athena, EMR, etc.). - Using data/task orchestration tools (Airflow). - Cloud computing-based data cloud solutions (Snowflake).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 4, 2026 · 55 days ago
- Recorded sightings
- 43
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
At Bynder, we don’t just store creative assets; we enable brands to deliver exceptional content experiences that drive business impact.
In an era of exploding content volume and complexity, the world’s most iconic brands, including Spotify, Campari, and Lacoste, trust Bynder as their single source of truth for creative content. Our industry-leading DAM platform serves as the strategic engine for brand governance and control.
We are leading the shift from management to AI-powered content orchestration. By integrating human-led, customizable AI Agents directly into our enterprise-grade infrastructure, we enable brands to augment their workforce and intelligently automate high-effort workflows without sacrificing brand integrity. We turn creative content into intelligent assets that accelerate personalization and drive measurable business outcomes.
Ready to grow your career by helping the world’s leading brands deliver exceptional content experiences? Join our global team of 600+ ‘Byndies’ and help 4,000+ organizations work smarter with their content. Explore this opportunity and apply now to join our team.
As a Data Engineer at Bynder you will work closely with Data Analysts, Data Scientists, Software Engineers and DevOps Engineers, and anyone who uses data driven insights in their work. We are looking for someone who will help us develop data pipelines and build self-serve data tools for our internal stakeholders and customers. In this role you will see the direct impact of your work on our initiatives in improving the Bynder product, growing the customer base, and providing insights to our internal stakeholders.
What will you do
Take a leading role in the improvement of our Data architecture by applying Data Mesh principles.
Develop, scale, maintain and deploy our data platform infrastructure in the cloud.
Take a leading role in applying Data Lineage and Governance throughout the organisation.
Support the entire Product & Engineering organisation in their data needs.
Develop custom ETL pipelines, detect anomalies, and create optimised aggregations for analysis and dash boarding.
What will you bring as a Data Engineer
Minimum of 5+ years of Data Engineering experience and furthermore hands-on experienced in:
Experienced fully in AI Native development.
Designing Data Platforms and taking architectural decisions, leading the way towards better data ecosystems.
Knowledge and experience in Data Mesh.
Knowledge and experience in Data Governance and Data Lineage best practices.
Developing data flows for the processing of data at scale.
Using industry standard data pipelining tools (Spark, Kafka).
Working with AWS (S3, Glue, Athena, EMR, etc.).
Using data/task orchestration tools (Airflow).
Cloud computing-based data cloud solutions (Snowflake).
Using infrastructure-as-code solutions (Terraform).
Partnering with cross-functional teams of engineers, data scientists and devops in defining a modern data architecture.
What will you bring as a colleague
A critical thinking mindset and the courage to speak your mind.
A growth mindset and the determination to improve yourself and others.
Great communication skills in English.
What we have
Challenging and inspiring work environment
Learning and Development budget
Commuting budget
Mental Health and Well-being Support
Bynder Love "stipend”
Unlimited vacation policy
Volunteer Time Off
Team and Company activities
Complimentary Lunches and Snacks
Our Commitment:
Bynder Love is the principle that guides the way we grow our teams, support our employees, and celebrate our differences. At Bynder we strive to create a culture that embraces every Byndie because differences in background, experience, and perspective makes Bynder even better. At Bynder a diverse, inclusive, and equitable workplace is one where all employees, whatever their ethnicity, color, sex, age, religion, disability, sexual orientation, gender identity, national origin or physical and mental ability are valued and respected. Our commitment is for all Byndies to have the freedom to be their true authentic selves.
Just as we are never finished innovating, Bynder’s dedication to being An Even Better Bynder is a constant, evolving commitment that includes education, listening, and action.
#LI-Hybrid #LI-MF1
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Barcelona, Spain
Just as we are never finished innovating, Bynder’s dedication to being An Even Better Bynder is a constant, evolving commitment that includes education, listening, and action. #LI-Hybrid #LI-MF1
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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