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 engineering while making a positive 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 opportunities for professional advancement and a collaborative environment where your contributions directly impact the future of AI-driven solutions in the health and wellness sectors. Join us in a fast-paced scale-up setting that encourages initiative and celebrates problem-solving, all while making a meaningful difference in people's lives.
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 refer you directly.
✨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 data warehousing best practices. Be ready to discuss how you've tackled real-world problems in your previous roles—pragmatic problem-solving is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. 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 to know you better. 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 brush up on your knowledge of GCP, SQL, and the tools mentioned like dbt, Fivetran, and Snowflake. Be ready to discuss how you've used these technologies in past projects, especially in building AI/ML applications.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your pragmatic problem-solving abilities. Think about times when you faced challenges in data engineering and how you navigated them, especially under real-world constraints.
✨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’re not just technically skilled but also aware of the ethical implications of your work.
✨Demonstrate a Growth Mindset
Be ready to talk about how you thrive in fast-paced environments and handle ambiguity. Share experiences where you took initiative and ownership of projects, showcasing your self-starter attitude.
