Senior Data Engineer

KUNGLIGA TEKNISKA HÖGSKOLAN

Vi etablerar nu Microsoft Fabric som kärnan i vår dataplattform och söker en senior data engineer som vill driva utvecklingen vidare. Är du redo att ta en nyckelroll i KTH:s resa mot smartare och mer datadrivna arbetssätt? Du är varmt välkommen med din ansökan! Om avdelningen/enheten Vi på verksamhetsstödet utvecklar kontinuerligt arbetssätt, processer och digitala stöd för att skapa bästa möjliga förutsättningar för universitetets utbildning och forskning. Hos oss får du möjlighet att bidra till denna utveckling och samtidigt utvecklas professionellt. Teamet Du kommer ingå i ett mindre team där du har stor möjlighet att ta ansvar, komma med idéer och utveckla såväl den egna som verksamhetens kompetens. I teamet ingår andra data engineers, objektledning, kravanalytiker samt arkitekter. Du kommer därtill ha nära samarbete med verksamheten i planerings- och leveransarbetet.   Arbetsuppgifter Som senior data engineer hos oss är du med i ett tidigt skede och formar KTH:s centrala analys- och dataplattform i Microsoft Fabric. Du kommer att arbeta i en miljö där forskning, utbildning och samhällsnytta är kärnan och du får ett stort ansvar och frihet att påverka och bidra till den framtida utvecklingen.   I rollen kommer du bland annat att:  Vara med och forma, vidareutveckla och framtidssäkra KTH:s dataplattform i Microsoft Fabric där datasäkerhet och behörighetsstyrning är en naturlig del av designen. Designa och sätta upp stabila integrationer för att kontinuerligt hämta in data från olika källor. Utforma vår Lakehouse-struktur enligt Medallion-arkitekturen och utveckla transformationer i PySpark med ett tydligt fokus på datakvalitet och användarvänlighet.  Skapa analysfärdiga dataprodukter, semantiska modeller och Power BI-rapporter som skapar värde för verksamheten. Arbeta strukturerat med versionshantering av kod och sätta upp smidiga leveransflöden (CI/CD) i Azure DevOps.  Kvalifikationer Krav Relevant akademisk utbildning eller på annat sätt förvärvade motsvarande kunskaper som arbetsgivaren bedömer som likvärdiga. Aktuell arbetslivserfarenhet av datamodellering samt att designa och bygga skalbara datalager och ETL/ELT-processer med Python/PySpark och SQL. Praktisk förståelse för och erfarenhet av plattformens kärnkomponenter såsom Data Pipelines, Notebooks, Lakehouse/Warehouse och semantiska modeller. Arbetslivserfarenhet av att använda och integrera mot och hantera API:er. Erfarenhet av att fånga upp och översätta affärskrav till tekniska lösningar samt visad förmåga och erfarenhet av att visualisera data i interaktiva dashboards (exempelvis Power BI). Goda kunskaper i svenska och engelska i såväl tal som skrift.   Personliga egenskaper  Tjänsten passar dig som är nyfiken och trivs med att utforska teknik och vara med och forma riktningen. Vi söker dig som är kvalitetsmedveten och vill bidra till hållbara lösningar. Vi ser att du har god samarbetsförmåga och bidrar till ett positivt arbetsklimat. Du visar gott omdöme i uttalanden, agerande och beslut samt har förmåga att balansera olika typer av hänsynstaganden. Vidare ser vi att du är strukturerad och självgående. Du kan göra avvägningar och prioriteringar samt vid behov ändra fokus.  Meriterande Microsoft Certified: Fabric Data Engineer Associate (DP-700) och/eller Microsoft Certified: Fabric Analytics Engineer Associate (DP-600). Erfarenhet av arbete i Microsoft Fabric samt Azure DevOps för versionshantering och CI/CD. Erfarenhet av att driva arkitektur och plattformsutveckling. Kunskap om datasäkerhet och regelefterlevnad.  Vi kommer lägga stor vikt vid personliga egenskaper. Bli en del av KTH   KTH formar framtiden genom utbildning, forskning och innovation. Som ett ledande internationellt tekniskt universitet spelar vi en aktiv roll i att driva och medverka i omställningen till ett hållbart samhälle. Här erbjuds du möjligheten att växa och utvecklas på en kreativ och dynamisk arbetsplats med goda arbetsvillkor och förmåner. Jämställdhet, mångfald och lika villkor är en kvalitetsfråga och en självklar del av KTH:s värdegrund som universitet och statlig myndighet. Läs mer om våra förmåner och hur det är att arbeta och utvecklas på KTH. Fackliga representanter Kontaktuppgifter till fackliga representanter. Ansökan Du ansöker via KTH:s rekryteringssystem. Du som sökande har ansvaret för att din ansökan är komplett när den skickas in och att de kvalifikationer vi efterfrågar i annonsen framgår i ditt CV. I denna rekrytering söker du endast med ditt CV. I stället för ett personligt brev kommer du i rekryteringssystemet att få besvara en eller flera frågor. Det är viktigt att du besvarar frågorna noggrant och sanningsenligt, för att vi ska få en tydlig bild av din kompetens och erfarenhet. Vi baserar vårt urval på kvalifikationerna som framgår av annonsen.  Ansökan ska vara KTH tillhanda senast sista ansökningsdagen vid midnatt, CET/CEST (CentralEuropean Time/Central European Summer Time). Om anställningen  Anställningen gäller tillsvidare enligt avtal. Anställningen inleds med sex månaders provanställning. Övrigt För information om behandling av personuppgifter i samband med rekrytering. Det kan förekomma att en anställning hos KTH är placerad i säkerhetsklass. Om så är fallet för just denna anställning görs en säkerhetsprövning av sökande i enlighet med säkerhetsskyddslagen (2018:585) efter samtycke. I dessa fall är en förutsättning för anställning att sökande blir godkänd efter säkerhetsprövning. Tester kan komma att tillämpas i denna rekryteringsprocess. Vi undanber oss direktkontakt med bemannings- och rekryteringsföretag samt försäljare av platsannonser.

Valtech

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.  THE OPPORTUNITY At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.  We are proud of:  * The work we do and the innovation we drive  * Our values of share, care and dare  * A workplace culture that fosters creativity, diversity and autonomy  * Our borderless, global framework, which enables seamless collaboration  The role   We are looking for an experienced Senior Data Engineer to design, build, and optimize modern, cloud-based data platforms that power analytics, AI, and data products across the organization. Beyond technical delivery, we're looking for someone genuinely curious about the business problems behind the data — someone who can apply common sense thinking, detailed analysis, and experience-based recommendations to help derive and shape business requirements, not just implement them as given. You will work on scalable batch, streaming, and near-real-time pipelines, enabling high-quality, curated datasets while ensuring robust data governance, security, and observability across the data ecosystem. You will also play a key role in supporting AI and GenAI systems, enabling pipelines for machine learning, causal modeling, and LLM-powered applications such as RAG and agent-based systems. Our preferred platforms are Microsoft Azure / Fabric (primary), GCP, AWS, Databricks, and Snowflake, with Azure experience being highly transferable to Fabric. You will collaborate closely with data scientists, ML engineers, and platform teams to ensure the data foundation supports production-grade, decision-oriented AI systems. Role responsibilities Build & Data Platform Engineering Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake). This includes developing reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake, and building ingestion, transformation, and curation workflows for both structured and unstructured data. You will implement modern data architectures including lakehouse patterns and medallion layering (bronze, silver, gold), ensuring systems are reusable, scalable, and aligned with enterprise needs. Enable AI, GenAI & Data Products Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems. You will enable data pipelines for GenAI use cases (including LLMs, RAG pipelines, and vector-based data flows), as well as agent-based architectures and intelligent workflows, ensuring that data is model-ready and production-grade. Data Modeling, Orchestration & Automation Design scalable logical and physical data models for analytical and operational use cases, ensuring consistency across domains. Orchestrate workflows using tools such as Airflow, dbt, Lakeflow, or equivalents, with strong focus on automation, reliability, and maintainability of end-to-end pipelines. Architecture, Governance & Observability Apply modern architecture patterns including event-driven and streaming architectures, and ensure adherence to best practices in data governance, lineage, quality, and access control (RBAC/ABAC). Establish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence, ensuring systems remain trustworthy and production-ready. Data Serving, Integration & Optimization Enable data serving layers (APIs, feature inputs, analytical endpoints) to support downstream systems, including ML and AI platforms. Continuously monitor and optimize pipelines and infrastructure for performance, scalability, and cost efficiency. Requirements Discovery & Business Partnership Bring genuine curiosity to every engagement — ask the right questions to understand not just what stakeholders are asking for, but why. Apply common sense thinking, detailed analysis, and experience-based recommendations to help derive and refine business requirements, surfacing gaps or better alternatives where they exist rather than simply executing a brief as written. Collaboration Work closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions. Support adoption of data products and contribute to best practices across the data and AI ecosystem. Must have qualifications Technical skills Strong hands-on experience with Apache Spark and Delta Lake, and strong programming skills in Python and SQL. Proven experience building batch and streaming data pipelines and production-grade data platforms, with solid understanding of data modeling, data quality, and governance principles. Cloud & Platforms (Key Requirement) Experience with one or more major cloud platforms, with preference for Microsoft Azure / Fabric, as well as AWS or GCP. Familiarity with modern data platforms such as Databricks and Snowflake is expected. Architecture & Systems Thinking Experience with lakehouse architectures and distributed data systems, and strong understanding of scalability, reliability, and performance considerations in data pipelines. Mindset Naturally curious, with strong problem-solving skills focused on scalability and reliability, and a collaborative approach to working in cross-functional teams. Comfortable applying common sense thinking, detailed analysis, and experience-based recommendations to help derive and challenge business requirements rather than taking them at face value. Experience in Agile or consulting environments is beneficial. Nice to have qualifications   Experience with GenAI and AI data systems (e.g., RAG pipelines, vector databases, LLM data preparation), as well as CI/CD for data pipelines and infrastructure-as-code tools such as Terraform, ARM, or CloudFormation.  Additional exposure to streaming technologies (e.g., Kafka), Spark optimization, or advanced analytics and ML workloads (including causal or experimentation platforms) is valuable. Experience building data products or large-scale analytics platforms is also beneficial.  Commitment to reaching all kinds of people  We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.  THE BENEFITS   This is a Full time position based in Ukraine.  Beyond a competitive compensation package, we offer:  * Mental and physical health: * Medical insurance  * Sports reimbursement budget  * Home office support  * A number of free psychological and legal consultations  * Maternity and paternity leave support  * Personal and professional development: * Internal workshops and learning initiatives  * English language classes compensation  * Professional certifications reimbursement  * Participation in professional local and global communities * Growth Framework to manage expectations and define the steps to move towards the selected career  * Mentoring program with the ability to become a mentor or a mentee to grow to a higher position  * Valtech Ukraine has a system of progressive benefits packages in place — the longer you stay with the company — the more benefits you get.  YOUR APPLICATION PROCESS Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential. ⚠️ Beware of recruitment fraud! We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.  ABOUT VALTECH Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.  At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.  At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.  Are you ready to create what’s next? Join us.

Valtech

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.  THE OPPORTUNITY At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.  We are proud of:  * The work we do and the innovation we drive  * Our values of share, care and dare  * A workplace culture that fosters creativity, diversity and autonomy  * Our borderless, global framework, which enables seamless collaboration  The role   We are looking for an experienced Senior Data Engineer to design, build, and optimize modern, cloud-based data platforms that power analytics, AI, and data products across the organization. Beyond technical delivery, we're looking for someone genuinely curious about the business problems behind the data — someone who can apply common sense thinking, detailed analysis, and experience-based recommendations to help derive and shape business requirements, not just implement them as given. You will work on scalable batch, streaming, and near-real-time pipelines, enabling high-quality, curated datasets while ensuring robust data governance, security, and observability across the data ecosystem. You will also play a key role in supporting AI and GenAI systems, enabling pipelines for machine learning, causal modeling, and LLM-powered applications such as RAG and agent-based systems. Our preferred platforms are Microsoft Azure / Fabric (primary), GCP, AWS, Databricks, and Snowflake, with Azure experience being highly transferable to Fabric. You will collaborate closely with data scientists, ML engineers, and platform teams to ensure the data foundation supports production-grade, decision-oriented AI systems. Role responsibilities Build & Data Platform Engineering Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake). This includes developing reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake, and building ingestion, transformation, and curation workflows for both structured and unstructured data. You will implement modern data architectures including lakehouse patterns and medallion layering (bronze, silver, gold), ensuring systems are reusable, scalable, and aligned with enterprise needs. Enable AI, GenAI & Data Products Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems. You will enable data pipelines for GenAI use cases (including LLMs, RAG pipelines, and vector-based data flows), as well as agent-based architectures and intelligent workflows, ensuring that data is model-ready and production-grade. Data Modeling, Orchestration & Automation Design scalable logical and physical data models for analytical and operational use cases, ensuring consistency across domains. Orchestrate workflows using tools such as Airflow, dbt, Lakeflow, or equivalents, with strong focus on automation, reliability, and maintainability of end-to-end pipelines. Architecture, Governance & Observability Apply modern architecture patterns including event-driven and streaming architectures, and ensure adherence to best practices in data governance, lineage, quality, and access control (RBAC/ABAC). Establish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence, ensuring systems remain trustworthy and production-ready. Data Serving, Integration & Optimization Enable data serving layers (APIs, feature inputs, analytical endpoints) to support downstream systems, including ML and AI platforms. Continuously monitor and optimize pipelines and infrastructure for performance, scalability, and cost efficiency. Requirements Discovery & Business Partnership Bring genuine curiosity to every engagement — ask the right questions to understand not just what stakeholders are asking for, but why. Apply common sense thinking, detailed analysis, and experience-based recommendations to help derive and refine business requirements, surfacing gaps or better alternatives where they exist rather than simply executing a brief as written. Collaboration Work closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions. Support adoption of data products and contribute to best practices across the data and AI ecosystem. Must have qualifications Technical skills Strong hands-on experience with Apache Spark and Delta Lake, and strong programming skills in Python and SQL. Proven experience building batch and streaming data pipelines and production-grade data platforms, with solid understanding of data modeling, data quality, and governance principles. Cloud & Platforms (Key Requirement) Experience with one or more major cloud platforms, with preference for Microsoft Azure / Fabric, as well as AWS or GCP. Familiarity with modern data platforms such as Databricks and Snowflake is expected. Architecture & Systems Thinking Experience with lakehouse architectures and distributed data systems, and strong understanding of scalability, reliability, and performance considerations in data pipelines. Mindset Naturally curious, with strong problem-solving skills focused on scalability and reliability, and a collaborative approach to working in cross-functional teams. Comfortable applying common sense thinking, detailed analysis, and experience-based recommendations to help derive and challenge business requirements rather than taking them at face value. Experience in Agile or consulting environments is beneficial. Nice to have qualifications   Experience with GenAI and AI data systems (e.g., RAG pipelines, vector databases, LLM data preparation), as well as CI/CD for data pipelines and infrastructure-as-code tools such as Terraform, ARM, or CloudFormation.  Additional exposure to streaming technologies (e.g., Kafka), Spark optimization, or advanced analytics and ML workloads (including causal or experimentation platforms) is valuable. Experience building data products or large-scale analytics platforms is also beneficial.  Commitment to reaching all kinds of people  We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.  THE BENEFITS   Beyond a competitive compensation package, we offer:  * Flexibility, with hybrid work options and 25 vacation days for a healthy work-life balance. * Co-subsidized transportation & Multisport cards. * Premium health insurance for fast and easy access to top healthcare services. * Training policy for technical and other skills-related events, courses and certifications. * Personal career development roadmap guided by performance evaluations. * Self-care program offering psychological consultations & discussions for you and the team. * Cozy office space designed for comfort and productivity. * Exciting team events and company gatherings. YOUR APPLICATION PROCESS Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential. ⚠️ Beware of recruitment fraud! We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.  ABOUT VALTECH Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.  At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.  At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.  Are you ready to create what’s next? Join us.