{"id":1947855,"url":"https://alion.io/job/valtech-senior-data-engineer-11","title":"Senior Data Engineer","company":{"id":8990,"name":"Valtech","domain":"valtech.com","url":"https://alion.io/company/valtech","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":76,"open_postings":17,"ghost_share":0.118,"stale_share":0.588,"repost_share":0.118,"time_to_fill_p50_days":57,"computed_at":"2026-10-06T05:45:30Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["BG","PL","MK","PT"],"hiring_countries_total":4,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":76000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1839},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Agile","optional":true},{"name":"Airflow","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"CI/CD","optional":true},{"name":"CloudFormation","optional":true},{"name":"dbt","optional":true},{"name":"Delta Lake","optional":true},{"name":"MLFlow","optional":true},{"name":"Python","optional":true},{"name":"SLI/SLO/SLA","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-06T07:05:07Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-06T21:59:02Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Why Valtech? We’retheexperienceinnovation company - atrusted partnerto the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careersand the chance to shape the future of experience. \nThe opportunity\nAt 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. \nWe are proud of: \nThe work we do and the innovation we drive \nOur values of share, care and dare \nA workplace culture that fosters creativity, diversity and autonomy \nOur borderless, global framework, which enables seamless collaboration \nThe role \nWe 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. \nYou 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. \nThis role can be delivered on either of our two core cloud ecosystems - AWS (with Databricks) or Azure/Fabric (with Databricks or native Fabric tooling) - and you'll be staffed on projects that match your strongest platform. You don't need experience in both. Additional experience across Snowflake or GCP is considered a strong plus. \nYou will collaborate closely with data scientists, ML engineers, and platform teams to ensure the data foundation supports production-grade, decision-oriented AI systems. \nRole responsibilities \nBuild & Data Platform Engineering \nDesign and implement scalable data platforms and pipelines on whichever of our two core ecosystems matches your strengths - AWS (with Databricks) or Azure/Fabric (with Databricks or native Fabric tooling) - with exposure to other environments (Snowflake, GCP) considered a plus. 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. \nYou will implement modern data architectures including lakehouse patterns and medallion layering (bronze, silver, gold) within Databricks or Fabric, ensuring systems are reusable, scalable, and aligned with enterprise needs. \nEnable AI, GenAI & Data Products \nDeliver 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 - leveraging Databricks' MLflow and Unity Catalog, or the equivalent Azure/Fabric and Azure ML tooling, depending on the platform you work in. \nData Modeling, Orchestration & Automation \nDesign scalable logical and physical data models for analytical and operational use cases, ensuring consistency across domains. Orchestrate workflows using tools such as Airflow, dbt, Databricks Workflows, Azure Data Factory, or equivalents, with strong focus on automation, reliability, and maintainability of end-to-end pipelines. \nArchitecture, Governance & Observability \nApply 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), using tools such as Unity Catalog and AWS Lake Formation, or Microsoft Purview, depending on the platform in use. \nEstablish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence, ensuring systems remain trustworthy and production-ready. \nData Serving, Integration & Optimization \nEnable 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 across our core cloud ecosystems. \nRequirements Discovery & Business Partnership \nBring 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. \nCollaboration \nWork 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. \nMust have qualifications \nTechnical skills \nStrong 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. \nCloud & Platforms (Key Requirement) - choose your track: \n Track A: Strong, demonstrable hands-on experience with AWS data services (e.g., S3, Glue, EMR, Redshift, Kinesis, Lambda) and the Databricks Lakehouse Platform \n Track B: Strong, demonstrable hands-on experience with Microsoft Azure / Fabric (e.g., Data Factory, Synapse, Fabric Lakehouse, Azure Databricks) \nYou only need deep expertise in one track - we treat both as equally weighted core platforms and will align you to projects based on where your experience is strongest. Familiarity with other modern data platforms such as Snowflake or GCP is a plus but not required. \nArchitecture & Systems Thinking \nExperience with lakehouse architectures and distributed data systems, and strong understanding of scalability, reliability, and performance considerations in data pipelines. \nMindset \nNaturally 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. \nNice to have qualifications \nDeep expertise in both tracks - AWS and Azure/Fabric, across Databricks and native Fabric tooling - is a strong plus, though not required, as is experience with GenAI and AI data systems (e.g., RAG pipelines, vector databases, LLM data preparation), CI/CD for data pipelines, and infrastructure-as-code tools such as Terraform or CloudFormation. \nAdditional 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. \nCommitment to reaching all kinds of people \nWe 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. \nThe benefits \nPrivate health insurance\nWe hope you will never need it, but nevertheless, we offer private health insurance to all our employees.\n\nEducation program\nWe never stop learning, that’s why we offer our employees an educational program with training and certification.\n\nWellbeing program\nWe all deserve to live a healthy and well-balanced life. It's not an option, it's a necessity!\n\nFree beverages\nEnjoy free coffee, drinks, and snacks at work, or join one of our famous company dinners.\n\nEvents\nWe enjoy spending time together, not only at work. Ski trips, carting, laser-tag, wine tasting, picnics, cooking classes… you name it - we’ve done it! There are plenty of cool events to join and to get to know your colleagues.\n\nCompetitive conditions\nBesides a competitive salary and 24 days of vacation, you will join annual company events with the whole team.\n\nChallenging projectsReady for a challenge? We guarantee you'll find challenging projects at Valtech!\n\nCool colleaguesWhat's the most important thing in a job? Cool colleagues with whom you spent most of the time during the week. We have a lot of them!\n\nHonest feedbackHonesty, openness and respect are among our core values. We encourage an open feedback culture in order to build trust and grow together.\n\nYour application process\nOnce 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.\nBeware of recruitment fraud!\nWe 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. \nAbout Valtech\nValtech 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. \nAt 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. \nAt 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. \nAre you ready to create what’s next? 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