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Data Engineer

  • Senior
  • Full-remote

As a Data Engineer at DKL, you will play a critical role in designing, building, and optimizing our data infrastructure. Working alongside cross-functional teams, you will develop reliable data pipelines and maintain the integrity of large datasets used for analysis and reporting, directly impacting data-driven decision-making across the company.

REMOTE

100%

You will work from the location of your choice, provided you structure this in a way that is compatible with work residency in Spain. You will also need to have a high-bandwidth internet connection (>= 40Mbs up/down). DKL has no physical headquarters: we take remote work very seriously, and our team is distributed in various parts of Spain and abroad.

SCHEDULE

Flexible

You will work 40 hours per week, with the flexibility to organize your schedule as you see fit. Requirements include sufficient overlap with the teams you collaborate with and attendance at dailies and occasional client meetings. We know that personal wellness is essential for achieving results.

COMPENSATION

40-60K

Opportunities to grow and advance your career. Every year, you will have €500 explicitly allocated for your educational needs.

100€ Amazon Gift Card on Christmas.

Vacations: 23 days/year.

    The role

    Learn about your responsibilities, how you will work, and who you will work with.

    As a Data Engineer at DKL, you will be responsible for developing, operating, and maintaining scalable data architectures that support analysis, reporting, AI, and machine learning applications. Your role will involve managing ETL processes, creating and running data warehouses, and ensuring the high performance and reliability of data systems. You will collaborate closely with product owners, data scientists, and analysts to translate business requirements into effective technical solutions while maintaining data quality and accessibility. As one of the primary contributors to DKL's data infrastructure, you will ensure our data solutions are efficient, accurate, and aligned with client goals.

    Responsibilities

    Your responsibilities will encompass a wide range of tasks, including but not limited to:

    How will you work?

    You will be part of DKL’s Data team, working remotely and collaborating with data scientists, analysts, and software engineers to support DKL’s data-driven goals. Daily check-ins and regular project meetings are held online, ensuring open communication and alignment throughout the project. Our data tools include Google Cloud Platform (GCP) and Microsoft Azure for cloud services, Databricks and Snowflake for big data processing and Data Warehousing, and Airflow for workflow orchestration. GitHub is used for version control and collaboration, while Jira and Confluence help with project management and documentation.

    Who will you work with?

    What makes you a fit?

    Your qualifications

    Requirements

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    Education

    Bachelor’s degree in Computer Science or a related field

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    Experience

    Proven experience in data engineering, including designing and maintaining data pipelines

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    Programming

    Strong Python programming and Software Engineering skills

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    Analytics

    Strong SQL and analytical skills

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    Cloud

    Proficiency with at least one of the leading cloud platforms (AWS, GCP, or Azure) and data warehousing tools (Snowflake, Databricks, Redshift, or BigQuery)

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    Orchestration

    Proficiency with a workflow orchestration tool, preferably Airflow

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    Governance

    Familiarity with data governance and security best practices

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    Collaboration

    Excellent problem-solving skills and the ability to both work independently and collaborate with a larger team in a remote setting

    Nice-To-Have

    • Experience with data streaming technologies, such as Kafka or Kinesis
    • Experience with machine learning pipelines and MLOps
    • Experience implementing a data mesh architecture
    • Experience with functional data engineering
    • Experience with Apache Spark
    • Experience with a Data Quality framework, such as Great Expectations
    • Experience using DBT to orchestrate SQL transformations in a Data Warehouse
    • Cloud or data engineering certifications
    • Previous experience in a fast-paced, agile environment

    What are the first 6 months like?

    Your first six months will be structured to support your learning, integration, and progression as you settle into your role. This period aligns with our review checkpoints at 1, 3, and 6 months, ensuring you have a clear pathway to success during your probation period.

    Month 1

    Your first month will focus on onboarding and getting grounded in our data platforms, engineering practices, and team workflows. You will have access to comprehensive technical documentation and training resources, meet key stakeholders across data, analytics, and product teams, and start familiarizing yourself with our data architecture, pipelines, and development tools. This phase is all about building a strong foundation—setting up your local environment, understanding our deployment processes, and reviewing active projects. At the end of the month, we will have a check-in to reflect on your experience, answer any technical or process-related questions, and ensure you have the support you need to move forward confidently.

    Months 2-3

    By month two, you will start taking on defined responsibilities within our data engineering projects, collaborating closely with your team to plan deliverables, estimate workloads, and coordinate progress across stakeholders. During this phase, you will begin owning smaller data pipelines or components within larger initiatives—whether that is building new data ingestion processes, optimizing existing workflows, or contributing to infrastructure improvements. This hands-on experience will help you build confidence with our tech stack and development practices. At the three-month mark, we will have a dedicated review to reflect on your progress, discuss any technical or operational challenges, and identify growth opportunities as you continue to deepen your impact on the team.

    Months 4-6

    With solid experience under your belt, by month four, you will be ready to lead your own data engineering projects more independently. During this stage, you will take ownership of end-to-end delivery—designing, building, testing, and deploying scalable data solutions that support our business needs. You will also focus on refining your technical skills, improving system performance, and contributing to best practices within the team. The six-month review will serve as a key milestone to evaluate your overall impact, technical growth, and collaboration while closing out the probation period and setting clear goals for your continued development within the team.

    What is the selection process?

    We aim to make our selection process smooth, informative, and enjoyable, ensuring it is a two-way street where we get to know each other.

    01/

    Initial Meet & Greet

    A casual video call to introduce ourselves, discuss the role at a high level, and get to know each other's backgrounds and motivations. This call is designed to determine if we are a good mutual fit.

    02/

    Role-Focused Interview

    A more focused discussion, diving into the role's specifics and exploring key data engineering scenarios you might encounter with us. This is where we will review some example cases, discuss your experience, and address any questions you may have about the day-to-day aspects

    03/

    Meet the Team Leads

    During this call, you will have the opportunity to meet some of our key team leads. This conversation helps you understand the company culture, our team dynamics, and the kind of cross-functional work you will be doing. It is also an opportunity to discuss the projects we are passionate about in more detail.

    04/

    Decision & Offer

    After the final discussion, we will circle back with a decision. If we are a good match, we will be excited to extend an offer and welcome you on board! If this is not the right fit, we will let you know and share our feedback, wishing you all the best on your career journey.

    Are you ready to take a new step in your career?

    Curious to find out more? Complete the formand send us your CV. And don't hesitate to ask questions!

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