Analytics Engineer

What will you do? As a Data Engineer at Rebtel, you will do more than build pipelines; you'll help shape the future of our data platform and influence how data is used across the company. At Rebtel, data sits at the heart of how we build products, understand customers, optimize growth, and make decisions. This is a hands-on engineering role with significant ownership. You'll work across our modern data stack, build scalable data products, and help define the architecture that supports analytics, automation, and future AI initiatives. If you're excited by clean architecture, modern data engineering practices, and solving meaningful business problems at scale; if you care about data quality and believe trust in data is built through engineering discipline; if you enjoy solving complex problems and turning ambiguity into practical solutions; and if you're excited to experiment with new technologies and approaches, we'd love to talk. Areas of ownership: Design, build, and maintain scalable, reliable data pipelines that power our Snowflake data platform Integrate data from a wide range of business and product systems Enable data activation across customer-facing and operational platforms, including CRM, customer support, and marketing tools Develop robust monitoring, alerting, and observability practices to ensure platform reliability Troubleshoot, optimize, and continuously improve data workflows and platform performance Design and implement scalable ELT workflows using modern data engineering practices Build well-structured dimensional models (facts and dimensions) that enable self-service analytics and reporting Implement automated testing and quality controls throughout the data lifecycle Ensure data is accurate, accessible, and trusted across the organization Work closely with analysts, product managers, engineers, marketers, and business stakeholders to understand data needs and deliver impactful solutions Help translate complex business challenges into scalable data products and datasets Support decision-making by making data easier to discover, understand, and use Evaluate emerging technologies, frameworks, and industry best practices Run proof-of-concepts and contribute to strategic technology decisions Help define the future architecture of Rebtel's data platform Continuously improve engineering standards, tooling, and developer experience Requirements: You are an excellent communicator and collaborator. We work in English, but you will hear many languages in our Stockholm office 3+ years of experience in Data Engineering or a similar role Strong SQL skills and experience building production-grade data pipelines Experience with modern ELT methodologies and data warehousing concepts Experience integrating data from multiple systems and sources Experience with dbt, Python, AWS, or similar cloud-based data platforms Strong understanding of data modeling and analytics engineering best practices Ability to operate independently and take ownership of technical solutions Experience working in fast-growing technology or digital product companies is a plus It's a bonus if you've been exposured to customer analytics, marketing analytics, experimentation, or machine learning workflows Experience with BI tools such as Looker, Tableau, or Power BI is a plus It's a plus with a degree in Computer Science, Engineering, Mathematics, or a related field Why Rebtel? Rebtel has been connecting people across borders for nearly 20 years. Today, we’re profitable, growing, and at a pivotal moment in our journey. As we enter our next phase, we’re building an organisation designed for speed, ownership, and real impact, where every role contributes directly to shaping what comes next. This is a place with global ambition and a strong foundation, where ideas move quickly and decisions matter. You won’t get lost in layers of process or slow-moving structures. Instead, you’ll find the space to take ownership, collaborate across teams, and make meaningful contributions from day one. Based in Stockholm, we bring together a diverse, international team united by a shared purpose: to simplify the way people connect worldwide. At Rebtel, you are the most important asset and we strive to provide a comprehensive package of benefits and perks that enhance your well-being and work experience. Here are some of the things you can expect from us: Pension Plan Health Checkups, Influenza shots and Private Medical Insurance Dental Insurance Occupational insurance Wellness allowance (5,000 SEK) Discount on gym memberships Bonus program Extra parental pay 30 days annual vacation Monday breakfasts Relocation Support, if you're joining us from afar, we'll assist you in making a smooth transition. We are Rebtel. We come from all around the world to create products for anyone who has crossed a border. We believe in equal opportunity and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Join the Data & AI journey at Schibsted Media Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands. In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams. You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases. About the role We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products. You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data. As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey. What you will do Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow Develop maintainable data models that support analytics, reporting, and AI use cases Contribute to good practices for data modeling, transformation, testing, documentation, and governance Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working Help improve reliability, performance, cost-efficiency, and scalability of our data solutions Participate in code reviews, technical discussions, and continuous improvement of our ways of working Contribute to a culture of ownership, learning, and collaboration What we are looking forMust have 3+ years experience as a Data Engineer, Analytics Engineer, or similar role Strong SQL skills and good understanding of data warehousing concepts Experience building data pipelines or data models for analytics, reporting, or product use cases Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar Ability to take ownership of tasks and deliver maintainable solutions Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language. Collaborative mindset and willingness to learn from and contribute to the team Nice to have Experience with Python or scripting for data engineering workflows Experience with Snowflake, dbt, Airflow, or similar tools Experience with CI/CD, version control, and engineering best practices Experience with cloud platforms such as AWS, GCP, or Azure Interest in data quality, observability, governance, or access control Experience working in a cross-functional or product-oriented environment Why join us? Opportunity to build trusted data products with real impact across Schibsted Media A role with ownership, learning opportunities, and support from experienced colleagues Flexible working hours and hybrid work options with strong trust and autonomy International environment with offices in Oslo, Stockholm, and Krakow Strong learning culture with learning budget and active engineering & AI communities Access to Schibsted’s media products, including premium news and podcasts About you You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value. You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful. When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content. If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.