.Bynder goes far beyond managing digital assets. Our digital asset management platform enables teams to conquer the chaos of proliferating content, touchpoints, and relationships in order to thrive. With powerful and intuitive solutions that embrace the way people want to work, and a richly integrated ecosystem, we are the brand ally that unifies and transforms the creation and sharing of assets, inspiring teams, delighting customers, and elevating businesses. Our 500+ employees, known as 'Byndies', together constitute the world's most extensive pool of digital asset management expertise. We enable more than 1.7M users across more than 3,700 organizations, including Spotify, Puma, Five Guys and Icelandair.About the role : Our SAAS platform is seen as one of the best in the DAM industry and we attribute a big part of our success to the talented and hardworking engineers we have in our tech teams. We are becoming one of the fastest-growing scale-ups of The Netherlands and have big plans and the ambition to be the fastest-growing scale-up in the world. This is why we are looking for a Data Engineer who would like to grow with us! As a data engineer at Bynder, you will work closely with analysts, DevOps, engineering, 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 :Develop, scale, maintain and deploy our data lake and data warehouse infrastructure in the cloud.Optimise the cost of managing and storing data.Advocate for Data Quality across the organization.Develop custom ETL pipelines, detect anomalies, and create optimised aggregations for analysis and dashboarding.What will you bring as a Data Engineer :Minimum of 3+ years of Data Engineering experience and furthermore hands-on experience in:Development data flows and processing data at scale.Using industry standard data pipelining tools (Spark, Kafka, Glue).Working with AWS (S3, Glue, Athena, Redshift, 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.Exposure to data science is also a plus.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
