We are a global scale-up from Barcelona, born in 2015, dedicated to changing the way the world uses energy. We envision a world free from fossil fuels and we believe the first step in this journey is creating solutions that make electric vehicle charging easier for everyone.
We’re devoted to researching and developing state-of-the-art electric vehicle charging solutions for homes, businesses, and cities. And this way, our mission is to create more sustainable ways of using and sharing energy.
We want to empower people to create, use and share renewable energy in ways they never imagined.
Wallbox currently operates in over 50 countries and has offices in Barcelona, Madrid, Shanghai, and San Francisco. We are powered by a culture of trust, innovation and diversity. For us, talent has no borders. We have more than 350 dedicated experts from over 30 different nationalities working together to create the most innovative products and the best experiences for our customers.
This culture has shown to be rewarding in many ways - amongst them, the creation of the world’s first bidirectional charger, the Quasar, and the recognition as the best of CES 2020 in transportation technology. We have recently closed our second tranche of Series A investment, bringing the total round to €23M and we’ve been recognized as LinkedIn's Top 5 Startups 2020 in Spain.
At the end of the day, working at Wallbox is at the same time challenging, fun and rewarding. If you like the idea of a dynamic environment, desire to work alongside an incredibly talented, fast-growing team and believe in the future of sustainable transportation, this is the place for you.
Are you ready to change the world with us?
About the role:
If you love data and SQL, want to work with a modern data stack (using technologies like Fivetran or Stitch, Airflow, dbt, Snowflake, GitLab CI, Spark and Kafka or Kinesis), love building datalakes and datawarehouses, believe the data team should adopt version control, data testing and data documentation processes or want to solve problems for the various areas of the company and make their lives easier, this is your opportunity!
As a Data Engineer at Wallbox, you are expected to be comfortable working to high standards as a professional data engineer, helping us to build and maintain a data platform that supports diverse use cases.
- Design, implement and grow our Wallbox Data Platform that ingests, stores, processes and exploits data from disparate data sources
- Design, implement, and orchestrate processes and components of data pipelines to support both real-time & batch analytics
- Give support to all different business units regarding data needs
- Govern all data ingested by the platform and define and implement high-performance, reusable, and scalable data models for our data warehouse to ensure that our end-users get consistent and reliable answers when running their own analyses
- Develop tools to monitor, debug, analyze and operate our data infrastructure and the quality of our datasets
- Ingest streaming data sources via an event bus like Apache Kafka or AWS Kinesis
- Deal with schema evolution with solutions such as a schema registry (like Confluent schema registry or AWS Glue schema registry) and data formats like Avro, Parquet or ORC
- Design, develop, and deploy Data Lakes in AWS
- Design complex queries in MySQL, in order to optimize performance of extraction and analysis of big datasets.
- Develop transformation jobs with a distributed computing framework like Apache Spark or SQL-based transformation framework like DBT
- Deploy Spark jobs in a distributed environment like AWS EMR or Databricks
- Automate data pipelines using tools like Apache Airflow
- Apply software engineering best practices like version control and continuous integration to the analytics code base.
- Coach analysts and data scientists on software engineering best practices
- 3+ years of experience working as part of a data team; preferably as a data engineer
- Hands-on and strong working knowledge of SQL
- Be fluent with one or more common data-related programming languages (Python, Java, Scala, or similar).
- Working experience with Amazon Web Services/Google Cloud Platform
- Experience with streaming platforms like Kafka or Aws Kinesis
- Experience with Apache Spark or Hadoop
- Experience with a Spark platform like AWS EMR or Databricks
- Be familiar with software development best practices and their applications to analytics (version control, testing, CI/CD, automation)
- Experience working with Data Scientists and Analysts
Nice to have:
- Experience with AWS Glue
- Experience with task orchestration tools (ex.Airflow, Luigi)
- Experience working with a modern data warehouse (Redshift, Snowflake, BigQuery, or similar)
- Experience with GitLab CI or Github actions
- Familiarity with infrastructure and automation tools (Terraform, Cloudformation, or similar)
- You are able to work-out effective solutions under uncertain or ambiguous circumstances
- You’re always willing to learn something new and embrace a healthy debate
- Quality in mind. You can easily detect whether a data result is good or bad in terms of quality and you understand that building good code with strong testing is key to growth and sustainability
- Strong analytical and problem-solving skills
- You have experience designing and implementing features in collaboration with product owners, reporting analysts/data analysts, and business partners within an Agile / Scrum methodology
- 100% company paid private medical insurance, including dental coverage, after six months
- Attractive compensation package
- Flexible working hours
- Friday afternoons off
- Opportunity to advance your payroll (under request)
- Unlimited coffee & beverages
- Language classes (English & Spanish)
- Sports channel, which offers online classes until our gym is opened
- Monthly “All Hands” & other team events
- Brand new canteen with a variety of breakfast and lunch dishes, everyday, for a discounted price
- Brand new offices in Zona Franca
- Over 20 different nationalities
- No suits! Unless it’s Carnival or Halloween
Please submit CV in English