At a Glance
- Tasks: Lead the design and management of data pipelines and AI-driven applications.
- Company: Join a forward-thinking company focused on responsible AI and data innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with a focus on collaboration and innovative problem-solving.
- Why this job: Shape the future of data infrastructure and make a real impact with AI.
- Qualifications: 5+ years in data engineering, advanced SQL, and GCP expertise required.
The predicted salary is between 70000 - 90000 € per year.
Requirements
- Experience building and deploying AI/ML-powered applications
- A solid understanding of responsible AI principles and how they apply to data infrastructure and product development
- 5+ years of commercial experience as a data engineer across multiple data products and pipelines
- Advanced knowledge of GCP as a data warehouse
- Advanced SQL skills with the ability to design and optimise complex queries at scale
- Deep familiarity with modern analytics and data architectures, including data warehousing best practices
- Experience with scalable backend systems and cloud platforms, with comfort across the full data engineering lifecycle — ingestion, cleaning, transformation and integration
- Experience with dbt, Fivetran and Snowflake
- Python proficiency
- Previous experience in health, wellness, pharmaceutical or digital/e-commerce sectors.
Nice to have
- Customer-focused: you are genuinely excited about building products that drive positive change at scale
- Self-starter: you use your own initiative, anticipate problems before they arise and take full ownership from raw ingestion to final delivery
- Pragmatic problem-solver: you take genuine pleasure in finding the right solution and making sensible trade-offs under real-world constraints
- Growth mindset: you thrive in fast-paced scale-up environments and are energised, not unsettled, by ambiguity and pace
What the job involves
- You will join our Data team as owner of our data infrastructure with an opportunity to architect and own the data pipelines, platforms and practices that will power our Data Platform
- A key part of this role is improving and defining how stakeholders can use AI to self-serve their own analysis
- You’ll sit at the intersection of data engineering and applied AI, working closely with analytics engineers and analysts
- You will define the standards and systems that allow the data team and stakeholders to self-serve analysis using AI as a base— ensuring the data foundation is reliable, scalable and ready to fuel our AI and LLM capabilities
- Build and maintain scalable data pipelines to ingest, transform and integrate data from multiple sources, defining best practice along the way
- Implement robust monitoring for data ingestion jobs and take swift corrective action when issues arise
- Work with business stakeholders to translate requirements into efficient pipeline architectures, database structures and optimised data models
- Partner with analytics engineers to ensure clean, accessible data is available to analysts across the organisation
- Champion responsible AI principles in the design and deployment of data systems that underpin our LLM and RAG implementations
- Lead on development standards, version control, quality control, deployment and change management processes
- Monitor, measure and maintain high data quality standards across all data products and pipelines
Lead Data Engineer employer: Deepstreamtech
As a Lead Data Engineer at our innovative company, you will thrive in a dynamic and supportive work culture that prioritises employee growth and development. We offer competitive benefits, including flexible working arrangements and opportunities to engage with cutting-edge AI technologies, all while being part of a team that is passionate about driving positive change in the health and wellness sectors. Join us in a fast-paced scale-up environment where your contributions will directly impact our data infrastructure and empower stakeholders to harness the power of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI/ML applications. This is your chance to demonstrate your advanced SQL skills and experience with data pipelines—make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of GCP and modern data architectures. Be ready to discuss how you've tackled real-world problems in previous roles, especially in health or e-commerce sectors.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely excited about building products that drive positive change.
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience with AI/ML applications and data engineering, especially if you've worked with GCP, SQL, or any relevant tools like dbt and Fivetran.
Showcase Your Projects:Include specific examples of projects where you've built scalable data pipelines or worked on data infrastructure. This is your chance to show us how you’ve tackled real-world problems and made a positive impact.
Be Authentic:Let your personality shine through in your application. We love self-starters who are excited about building products that drive change, so don’t be afraid to share your passion for data and AI!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application and get you into our system quickly. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you’re well-versed in GCP, SQL, and the tools mentioned like dbt, Fivetran, and Snowflake. Brush up on your AI/ML knowledge too, as you'll need to demonstrate how these technologies can be applied in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in previous roles, especially in data engineering. Be ready to discuss specific instances where you made trade-offs or found innovative solutions under pressure.
✨Understand Responsible AI Principles
Familiarise yourself with responsible AI principles and be prepared to discuss how they apply to data infrastructure. This will show that you not only have technical skills but also a strong ethical grounding in your work.
✨Communicate Like a Pro
Since you'll be working closely with stakeholders, practice explaining complex technical concepts in simple terms. Being able to translate technical jargon into layman's terms will set you apart and demonstrate your customer-focused mindset.
