{"id":2947757,"url":"https://alion.io/job/getfrankly-principle-data-engineer","title":"Principle Data Engineer","company":{"id":673186,"name":"GetFrankly","domain":"getfrankly.co","url":"https://alion.io/company/getfrankly","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":{"grade":"A","score":91,"open_postings":6,"ghost_share":0,"stale_share":0.167,"repost_share":0,"time_to_fill_p50_days":69,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Cluj-Napoca, Romania"],"countries":["RO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":75000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2491},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Great Expectations","optional":false},{"name":"Kubernetes","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Git","optional":true}],"status":"live","first_seen_at":"2026-10-20T15:41:22Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-22T18:58:19Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Core details\nCompany type: International Retail Group - In-house Data & Engineering\n\nLocation: Cluj-Napoca, Romania\n\nWork model: Hybrid\n\nEngagement: Employment Contract, Permanent, Full-Time\n\nRole level: Principal level - Senior Individual Contributor\n\nExperience level: 8+ Years\n\nKey Skills / Tech Stack: Python, SQL, Spark / PySpark / Scala, dbt, Databricks, BigQuery, Azure Data Factory, GCP / Azure / AWS, CI/CD, Terraform, Docker / Kubernetes, Great Expectations, data architecture (batch, streaming, event-driven)\n\nDepartment: Engineering / Data\n\nIndustry: Retail / Tech and digital\n\nAbout the client\nOur client is a large international retail group with an in-house engineering organisation - technology is built internally, not outsourced. Teams own what they design and run, end to end, on platforms that serve the group’s markets and brands across Europe.\nThe Cluj engineering hub is part of a wider international ecosystem. The data function is going through a period of transformation, and the local capability continues to grow.\nAbout the role\nAs Principal Data Engineer, you are the go-to technical authority for data engineering across the organisation. This is a senior individual contributor role, not a people management one. Your influence comes from expertise, direction and the standards you set, across multiple squads and domains.\nYou will define the data platform and data engineering strategy, own architecture decisions and patterns, and shape long-term roadmaps together with Architecture and Product. You will work with senior stakeholders across Engineering, Product, Architecture and the Tech Board, and lead complex initiatives that span systems, teams and geographies.\nYou will also be a central figure in the Data Engineering Chapter. You will mentor engineers, contribute to hiring and capability planning, and build a culture of learning, experimentation and technical excellence.\nResponsibilities:\nDefine and lead the data platform and data engineering strategy, aligned with wider technology objectives.\n\nOwn architecture decisions, patterns and standards across data pipelines, storage and processing.\n\nEstablish and evolve data engineering principles, frameworks and best practices.\n\nPartner with Architecture and Product to shape long-term roadmaps and platform capabilities.\n\nEnsure solutions are scalable, resilient, performant and cost-efficient.\n\nDrive the design and implementation of production-grade data pipelines and platforms.\n\nChampion modern engineering practices (CI/CD, testing, observability, DevOps) and standards for data quality, governance and security.\n\nPromote reuse through data products, shared services and platform capabilities.\n\nAct as technical leader across multiple squads, providing clear direction and decision-making guidance.\n\nLead large-scale, business-critical data initiatives, balancing speed, quality, cost and risk.\n\nMentor and coach engineers across the Data Engineering Chapter, and contribute to hiring and onboarding.\n\nStay ahead of industry trends, bring in new tools and approaches where they add value, and challenge existing ways of working.\n\nQualifications:\nStrong experience with distributed data processing systems and architectures.\n\nProven track record delivering large-scale data platforms and pipelines.\n\nExpertise in data modelling, storage, access and processing patterns.\n\nDeep understanding of data architecture patterns (batch, streaming, event-driven) and cloud-native, distributed systems design.\n\nExperience designing for resilience, scalability, observability, performance and cost efficiency.\n\nStrong Python and SQL, with Spark / PySpark (Scala is a plus).\n\nHands-on experience with dbt and modern data platforms such as Databricks, BigQuery or Azure Data Factory.\n\nExperience with at least one major cloud platform (GCP, Azure or AWS).\n\nDevOps / DataOps experience: CI/CD, Git, Terraform, Docker / Kubernetes.\n\nFamiliarity with data quality and testing frameworks such as Great Expectations.\n\nAbility to influence at executive level and across domains, and to lead through ambiguity and transformation.\n\nA track record of coaching engineers and raising capability across teams.\n\nExcellent English, written and spoken.\n\nAbout the offer\nOur client offers a competitive package and room to grow:\nAnnual performance bonus and employee referral bonus\n\nPrivate medical coverage through Regina Maria - Priority Plan, extendable to your spouse or children at no additional cost\n\nLife insurance through Metropolitan Life\n\nEyeglasses vouchers and a co-funded 7Card fitness membership\n\nAccess to LinkedIn Learning, LEO Learning and Bookster\n\nMeal vouchers, plus gift vouchers on several occasions throughout the year\n\nAdditional days off when public holidays fall on weekends\n\nPaid leave for special life events\n\nHybrid working model and a flexible schedule\n\nModern, collaborative workspace with fresh fruit and premium coffee","description_format":"text","description_chars":4920,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Flexible schedule","Hybrid work","Life insurance"],"hiring_locations":[{"name":"Romania","iso":"RO","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-20T19:10:34Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.542,"p_room":1,"age_days":1,"expected_fill_days":69,"reasons":["conf:0","agency","velocity","win:early"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/getfrankly-principle-data-engineer","json_url":"https://alion.io/job/getfrankly-principle-data-engineer.json","meta":{"generated_at":"2026-10-22T20:46:26Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":4918,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":673186},"rest":"https://alion.io/mcp/rest/get_company?id=673186"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgetfrankly-principle-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fgetfrankly-principle-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fgetfrankly-principle-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/getfrankly-principle-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgetfrankly-principle-data-engineer"}]}