Senior Data Engineer
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What you'll do
- Build Scalable Data Pipelines: Design, develop, and optimize robust data pipelines, making data easily accessible for visualization and machine learning applications.
- Leverage Cutting-Edge Technologies: Work with cloud-based platforms and big data processing tools to create scalable and efficient solutions.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, ML engineers, and analysts in an agile environment to deliver impactful data-driven solutions.
- Partner with Industry Leaders: Integrate best-in-class data solutions by working with Google Cloud Platform, dbt, and Looker.
- Manage Cloud Infrastructure: Architect, maintain, and troubleshoot cloud-based infrastructure to ensure high availability and performance.
- Lead and Mentor Team Members: Provide guidance and mentorship to engineers, supporting their professional development and ensuring best practices in data engineering.
What they're looking for
- Strong Programming Skills: Expertise in Python and/or Java, with proficiency in SQL.
- Experience in Data Engineering: 5+ years of experience in designing and building scalable data solutions.
- Passion for Data and Analytics: A deep interest in optimizing data workflows and making data-driven decisions.
- Expertise in ETL and Big Data: Hands-on experience with ETL tools, Hadoop-based technologies (e.g., Spark), and data processing frameworks like Beam or Flink.
- High-Quality Code Standards: Ability to write tested, resilient, and well-documented code.
- Cloud Computing Experience: Experience in building and maintaining cloud infrastructure (GCP or AWS is a plus).
- Problem-Solving Mindset: Ability to take ownership and drive projects from concept to completion.
- Strong Communication & Collaboration: Excellent interpersonal skills, with a team-oriented and proactive approach.
- Leadership & Mentorship Skills: Experience in line management and mentoring engineers, helping to grow the team’s technical capabilities.
Nice to have
- Start-Up/Scale-Up Experience: Previous experience working in a start-up or scale-up environment
- Command Line & Scripting: Love for the command line and experience with Linux scripting.
- API Development Experience: Experience building scalable REST APIs using Python or similar technologies.
- Machine Learning Knowledge: Knowledge or experience in machine learning, data mining, statistics, and visualization.
- Client-Facing Role: Prior experience in a client-facing position
- Open Source Contributions: Experience contributing to open-source projects.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Shape the Future of AI & Data with Us
At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
Your Mission
As a Data Engineer, your mission is to design and develop scalable, high-performance data pipelines that enable seamless data processing, visualisation, and integration into machine learning models.
You'll play a key role in shaping the data engineering foundation of our next-generation AI-driven products, ensuring that data flows efficiently and is readily accessible for advanced analytics.
What You’ll Do
Build Scalable Data Pipelines: Design, develop, and optimize robust data pipelines, making data easily accessible for visualization and machine learning applications.
Leverage Cutting-Edge Technologies: Work with cloud-based platforms and big data processing tools to create scalable and efficient solutions.
Collaborate with Cross-Functional Teams: Work closely with data scientists, ML engineers, and analysts in an agile environment to deliver impactful data-driven solutions.
Partner with Industry Leaders: Integrate best-in-class data solutions by working with Google Cloud Platform, dbt, and Looker.
Manage Cloud Infrastructure: Architect, maintain, and troubleshoot cloud-based infrastructure to ensure high availability and performance.
Lead and Mentor Team Members: Provide guidance and mentorship to engineers, supporting their professional development and ensuring best practices in data engineering.
What You’ll Bring
Strong Programming Skills: Expertise in Python and/or Java, with proficiency in SQL.
Experience in Data Engineering: 5+ years of experience in designing and building scalable data solutions.
Passion for Data and Analytics: A deep interest in optimizing data workflows and making data-driven decisions.
Expertise in ETL and Big Data: Hands-on experience with ETL tools, Hadoop-based technologies (e.g., Spark), and data processing frameworks like Beam or Flink.
High-Quality Code Standards: Ability to write tested, resilient, and well-documented code.
Cloud Computing Experience: Experience in building and maintaining cloud infrastructure (GCP or AWS is a plus).
Problem-Solving Mindset: Ability to take ownership and drive projects from concept to completion.
Strong Communication & Collaboration: Excellent interpersonal skills, with a team-oriented and proactive approach.
Leadership & Mentorship Skills: Experience in line management and mentoring engineers, helping to grow the team’s technical capabilities.
Bonus Points If You Have:
Start-Up/Scale-Up Experience: Previous experience working in a start-up or scale-up environment
Command Line & Scripting: Love for the command line and experience with Linux scripting.
API Development Experience: Experience building scalable REST APIs using Python or similar technologies.
Machine Learning Knowledge: Knowledge or experience in machine learning, data mining, statistics, and visualization.
Client-Facing Role: Prior experience in a client-facing position
Open Source Contributions: Experience contributing to open-source projects.
What’s in It for You?
We believe in empowering our team to thrive, with benefits including:
Holiday: 30 days plus bank holidays (obviously!)
Health Perks: 4500 kr per year Healthcare Allowance (paid monthly, after probation)
Fitness & Wellbeing: Up to 5000 kr per year Wellness Allowance (payable on receipt of invoice)
Hybrid Model: 1200 kr WFH Equipment Allowance (after probation)
Learning & Growth: Access to platforms like Udemy to fuel your curiosity.
Pension: Private Salary Sacrifice Pension available
Why Datatonic?
Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn’t just encouraged - it’s embedded in everything we do. If you’re ready to inspire change and deliver value at the forefront of data and AI, we’d love to hear from you!
Are you ready to make an impact?
Apply now and take your career to the next level.
Company
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