Data Engineer (MAD)


Job Description

We are looking for software engineers with one to three years of experience and a passion for data. We expect our data engineers to keep learning new technologies, architectural patterns, programming languages and machine learning algorithms. They will work with data scientists and are comfortable speaking their language. We are looking for professionals who are enthusiastic about innovation in software engineering and are not afraid to contribute to open-source projects and present their work at technical meetups. As we help our clients to target, measure and improve mission-critical business metrics and generate demonstrable return on investment, our data engineers enjoy a high level of responsibility and immediate client interactions. In addition to technical excellence, our engineers are great communicators equipped with the presentation skills to operate at executive level. Above all, our engineers are curious about the big picture and passionate about bringing data to life! Our products Together with data science and data analytics team we make our customers happy. We design and build data warehouse and data lakes for processing large amounts of data, integrate applications, maintain ML pipelines, help data science team with experiments. Our technology stacks We use Azure, AWS and Google cloud services. In most of the cases we build big data of fast data- oriented solutions, by this reason, we use Kinesis, Lake Formation, Athena, Redshift, Glue, Azure Functions, Events Hub, Data Factory, SageMaker, BigQuery, BigTable, DataFlow etc. For on premise solutions, we use Hadoop stack, ELK stack, Postgres, SQL Server, Kafka, NoSQL solutions like Cassandra, Redis, Aerospike etc. We prefer to build applications on Python, occasionally Scala or R.


  • Engineers complete technical solutions to solve concrete business challenges in the areas of digital marketing, eCommerce, Business Intelligence and self-service analytics.
  • Support our clients in executing their Big Data strategies by designing and building operational data platforms: ETL pipelines, data anonymization pipelines, data lakes, near real-time streaming data hubs, web services, training and scoring machine learning models.
  • Collaborate closely with partners, strategy consultants and data scientists in a flat and agile organization where personal initiative is highly valued.

Required Experience

  • 1-3 years of professional experience in software engineering
  • A broad practice in multiple software engineering fields:
  • Backend and/or frontend development in any programming language of your choice
  • Design of web services
  • Algorithms and complexity analysis
  • Linux system administration, development and production environments
  • Cloud, container and microservices infrastructures
  • Software security
  • Development workflow automation
  • Ability to work in the English language with strong written and oral communication skills
  • Based in Madrid, willingness to travel is required.