At a Glance
- Tasks: Design and develop scalable data models to drive business insights and performance.
- Company: Join a forward-thinking tech company that values collaboration and innovation.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Diverse team environment with a focus on continuous improvement and career advancement.
- Why this job: Be at the forefront of data analytics, influencing key business decisions and strategies.
- Qualifications: Expertise in SQL, data modelling, and a strong understanding of analytics methodologies.
The predicted salary is between 50000 - 65000 € per year.
Requirements
- SQL Proficiency: Expert level, with the ability to debug complex queries
- Advanced Data Modelling: Experience building sophisticated, reusable, and scalable dimensional models
- Technical Governance: Proven track record of influencing technical guidelines and conducting rigorous code reviews
- Analytics Methodology: Strong knowledge of attribution modelling and cohort analysis
- Operational Excellence: Experience in pipeline design and reliability engineering, including advanced observability
- Domain Expertise: Significant experience in Marketing, CRM, or customer-focused analytics
We welcome applications from diverse and varied backgrounds so get your application in and let’s chat!
What the job involves
- We work together with your team and the people you will work with
- You will join the Technology & Product function within the Data family
- This role acts as a strategic partner to core business units such as product, operations, commercial, or customer functions
- You will sit at the intersection of data engineering and business strategy, working closely with both technical peers and non-technical stakeholders to translate ambiguous problems into clear analytical frameworks
- As an Analytics Engineer, you will take end‑to‑end ownership of the reliability and performance of core analytical domains
- Designing and developing robust, scalable data models that enable high-quality analytics across UW
- Identifying opportunities for revenue growth and cost reduction by translating data into strategic recommendations
- Defining and tracking key metrics to measure business performance and success
- Designing experiments to evaluate and support continuous business improvement
- Influencing the roadmap and driving measurable improvements in core business KPIs
- Addressing technical debt and balancing the trade‑off between "shipping fast" and "building right"
Analytics Engineer employer: Deepstreamtech
As an Analytics Engineer at our company, you will thrive in a dynamic and inclusive work culture that values collaboration and innovation. We offer competitive benefits, opportunities for professional growth, and the chance to work at the forefront of data-driven decision-making in a vibrant location. Join us to make a meaningful impact while developing your skills alongside a diverse team of experts.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews! Research the company and practice common interview questions. We suggest you also think about how your skills in SQL and data modelling can directly benefit their business goals.
✨Tip Number 3
Show off your projects! If you’ve built any cool data models or conducted interesting analyses, make sure to share them during your conversations. We love seeing real-world applications of your skills!
✨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’re always on the lookout for diverse talent to join our team!
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Show Off Your SQL Skills:Make sure to highlight your expert-level SQL proficiency in your application. We want to see how you can debug complex queries and tackle any data challenge that comes your way!
Demonstrate Your Data Modelling Experience:When writing your application, share examples of sophisticated, reusable, and scalable dimensional models you've built. This will show us that you have the advanced data modelling skills we’re looking for.
Highlight Your Technical Governance Knowledge:Don’t forget to mention your experience with technical guidelines and code reviews. We value candidates who can influence best practices and ensure high-quality outputs in our analytics processes.
Connect Your Experience to Our Needs:Tailor your application to reflect your domain expertise in Marketing, CRM, or customer-focused analytics. Show us how your background aligns with our goals, and don’t hesitate to apply through our website!
How to prepare for a job interview at Deepstreamtech
✨Master Your SQL Skills
Since SQL proficiency is a must for this role, make sure you brush up on your skills. Practice debugging complex queries and be ready to discuss your thought process during the interview. You might even want to prepare a few examples of how you've tackled tricky SQL problems in the past.
✨Showcase Your Data Modelling Experience
Be prepared to talk about your experience with advanced data modelling. Bring examples of sophisticated, reusable, and scalable dimensional models you've built. Highlight how these models have contributed to analytics and decision-making in previous roles.
✨Demonstrate Technical Governance Knowledge
Technical governance is key in this position, so come armed with examples of how you've influenced technical guidelines or conducted code reviews. Discuss any frameworks or best practices you've implemented to ensure high-quality code and maintainability.
✨Connect Data to Business Strategy
This role sits at the intersection of data engineering and business strategy, so be ready to explain how you've translated data insights into strategic recommendations. Share specific instances where your analytical work has led to revenue growth or cost reduction, and how you measured success.
