{"id":676032,"url":"https://alion.io/job/camlin-senior-data-engineer","title":"Senior Data Engineer","company":{"id":668999,"name":"Camlin","domain":"camlin.co","url":"https://alion.io/company/camlin","size_band":"501-1000","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"A","score":86,"open_postings":22,"ghost_share":0,"stale_share":0.545,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-24T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Parma, Italy"],"countries":["IT"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":52000,"max_usd":126000,"period":"year","method":"role_seniority_country_cell","sample_n":8},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Databricks","optional":true},{"name":"MLFlow","optional":true},{"name":"Python","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2024-04-24T11:51:46Z","employer_posted_date":"2024-04-24","last_verified_at":"2026-09-25T01:10:30Z","board_verified":true,"closed_at":null,"days_open":883,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":882},"description":"About Camlin Group:\nCamlin develops industrial technology and AI-driven systems used across the energy sector in more than 20 countries. We work on difficult real-world problems involving critical infrastructure, industrial sensor networks, and operational intelligence.\nWe are looking for a Senior AI & Data Engineer to help design and deliver AI and data products focused on predictive maintenance, anomaly detection, asset monitoring, and energy forecasting. This is a hybrid working permanent role (3 days on-site, 2 days work from home).\nThis is a highly hands-on engineering role for someone who enjoys solving difficult AI and data problems in real operational environments. You’ll work closely with domain experts, product stakeholders, and engineers to turn data into reliable systems that create measurable business impact.\nWe are looking for someone who can combine strong technical execution with the ability to bring structure, clarity, and momentum to complex engineering initiatives. You’ll play an important role in shaping technical plans and driving delivery across AI and data projects.\nWhat you'll work on:\nYou’ll help build AI and data products used in energy environments, including:\nPredictive maintenance systems for critical infrastructure\nAnomaly detection on sensor data\nAsset monitoring and operational intelligence platforms\nEnergy forecasting and time-series modelling systems\nProduction ML systems operating on large-scale multimodal datasets\nThe work involves difficult real-world constraints:\nNoisy and incomplete sensor data\nSparse labels and uncertain signals\nLarge-scale time-series datasets\nScaling AI systems into real world solutions\nTranslating unclear requirements into practical delivery plans\nWhat you'll do:\nDesign and build AI and data systems from early concept through model creation \nWork closely with data scientists, product managers, and domain experts to shape technical solutions\nTurn ambiguous business and operational problems into structured engineering plans\nPrototype and validate ideas quickly to reduce technical and product risk early\nBuild scalable data and ML workflows using modern cloud-native tooling\nInfluence technical direction, architecture decisions, and product roadmap discussions\nEvaluate trade-offs between model accuracy, reliability, complexity, latency, and operational cost\nHelp drive measurable outcomes with clear KPIs and visible business impact\nImprove engineering quality, maintainability, and operational reliability across the stack\nOur current tech stack includes:\nPython\nApache Spark\nDatabricks\nMLflow\nModern cloud-based data platforms\nLarge-scale industrial and time-series datasets\nWhat you'll need:\nA relevant degree\nExperience building real-world AI, ML, or data products\nExperience working across data engineering and ML systems, not just isolated pipelines\nComfortable operating in environments with uncertainty and evolving requirements\nPragmatic engineering mindset focused on outcomes and business impact\nAbility to make and communicate trade-offs clearly\nSystems thinker who can connect architecture, product goals, and operational constraints\nStrong communication skills with both technical and non-technical stakeholders\nCollaborative approach with a willingness to challenge assumptions constructively\nThis role is probably not a good fit if you:\nPrimarily identify as a pipeline-only or ETL-focused engineer\nPrefer fully specified requirements before starting work\nWant narrowly scoped responsibilities without product or technical ownership\nThis role starts as a senior individual contributor position with strong technical influence. Over time, the expectation is that you will increasingly shape technical plans, mentor engineers, and take ownership of larger AI and data initiatives across the organization.\nSuccess in this role means:\nDelivering AI systems that create measurable operational value\nReducing uncertainty and technical risk early\nHelping teams make better engineering and product decisions\nBuilding trust across engineering, product, and domain teams\nDriving predictable delivery in complex industrial environments\nWhy this role stands out:\nWork on unusual industrial and energy datasets\nBuild AI capabilities with visible business impact\nSolve technically challenging real-world problems\nOperate with meaningful ownership and influence\nHelp shape the future direction of AI systems in critical infrastructure\nBenefits:\nDaily food vouchers: for days worked in person in the premises.\nTraining Support: We offer financial assistance for your training and development, based on company discretion. We also have an internal training platform to support your professional and personal development.\nDiscounted Gym Membership: Stay fit with our discounted gym membership program.\nWellness Programs: We prioritise your well-being through our wellness initiatives.\nInternal Reward & Recognition Tool Kudos: This streamlines and automates the process of acknowledging and appreciating employees and helps contribute to our positive workplace culture.\nOur Values\nWe work together\nWe believe in people\nWe won’t accept the ‘way it’s always been done’\nWe listen to learn\nWe’re trying to do the right thing\nEQUAL EMPLOYMENT OPPORTUNITY STATEMENT\nIndividuals seeking employment at Camlin are considered without regards to race, colour, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, gender identity, or sexual orientation.","description_format":"text","description_chars":5475,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Gym membership","Hybrid work","Wellness"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Event Management","Logistics","Venues"],"lifecycle":[{"event":"open","at":"2026-09-10T22:53:18Z"}],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":1,"p_active":0.189,"p_room":0.28,"age_days":882,"expected_fill_days":42,"reasons":["conf:3","stale_co","velocity","win:tail","crowd:"],"computed_at":"2026-09-24T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/camlin-senior-data-engineer","json_url":"https://alion.io/job/camlin-senior-data-engineer.json","meta":{"generated_at":"2026-09-25T04:01:13Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4356,"day_limit":5000,"remaining_today":644,"minute_limit":60,"resets_at":"2026-09-26T00:00:00Z"}}}