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Day 61
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Barcelona · Barcelona, Spain
Live, first seen by us 61 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: R&D › EngineeringFrom the employer’s posting
Do you require visa sponsorship or a visa transfer?From the employer’s application form
Lead 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
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.
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).
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 61
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 10,805 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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).
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
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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
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