{"id":3887830,"url":"https://alion.io/job/hireflex-senior-data-engineer","title":"Senior Data Engineer","company":{"id":4442813,"name":"HireFlex","domain":"hireflex.in","url":"https://alion.io/company/hireflex","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":null,"truth_index":null},"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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Aurora","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"Grafana","optional":true},{"name":"Power BI","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-06T17:32:46Z","employer_posted_date":null,"last_verified_at":"2026-11-06T17:32:46Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"(Senior) Data Engineer – D&A Product (Packaging, Brewing & Utilities)\nGlobal Digital & Technology (D&T) – Supply Chain \nRole Purpose\nAs a (Senior) Data Engineer within HEINEKEN's D&A Product Organisation, you play a key role in enabling the Smart Brewery vision. You are embedded in a cross‑functional product squad (Connected Brewery, Packaging, Brewing, or Utilities), working under the functional direction of the Product Lead and in close collaboration with Business Analysts, BI Developers, Data Scientists, and Brewery SMEs.\nYou transform operational and analytical needs into robust, scalable, and globally reusable data pipelines, data models, and foundational datasets. These assets power diagnostics, reporting, advanced analytics, optimisation, and predictive capabilities across our breweries.\nYou ensure data is reliable, trusted, performant, and aligned with global D&A standards.\nYou bring strong engineering craftsmanship, technical leadership, and structured problem‑solving to elevate our global data foundations. Through active engagement in Agile Ways of Working, you ensure every increment delivered by the squad is high‑quality, maintainable, and business‑relevant.\n\nKey Responsibilities\n1. Product Discovery & Requirements\nAssess feasibility of new use cases by analysing data availability, structure, quality, and integration needs.\nTranslate operational and analytical needs into clear data engineering requirements, data flow designs, and technical tasks.\nCollaborate with Product Leads, Business Analysts, and Developers to shape a structured and prioritised backlog.\nContribute to the definition and refinement of global, reusable data components and standards aligned with the D&A roadmap.\nParticipate in the technical assessment of new ideas and enhancement requests (Idea Portal, SNOW).\nProvide L2 technical support for use case–related queries and incidents, ensuring timely resolution and knowledge development.\n\n2. Stakeholder Engagement\nCommunicate data pipeline logic, architecture decisions, and engineering constraints clearly to technical and non‑technical audiences.\nCollaborate closely with Business Analysts, SMEs, and BI Developers to ensure KPI logic, data semantics, and models align with available data and technical reality.\nSupport alignment sessions on data structures, data flows, governance rules, and metric definitions.\nAct as a (senior) engineering voice ensuring solutions are high‑quality, future‑proof, and operationally relevant.\n\n3. Data & Analytics Enablement\nDesign, build, and operate scalable, serverless data pipelines using AWS and Azure technologies (e.g., Lambda, Glue, Step Functions, S3, DynamoDB, Aurora).\nDevelop and maintain Python ETL packages, including logging, lineage, validation, transformation logic, and reusable components.\nImplement high‑quality data models and semantic layers aligned with HEINEKEN D&A standards.\nPartner with BI Developers to provide the right data structures for dashboards, KPIs, semantic models, and analytical products.\nIdentify data quality issues and collaborate with Business Analysts and SMEs to investigate, fix, and prevent reoccurrence.\n\n4. Product Delivery & Value Realisation\nDeliver high‑quality, fully tested engineering increments meeting acceptance criteria and the squad's Definition of Done.\nContribute to the engineering development lifecycle: build → test → validate → document.\nSupport sprint reviews and demos by explaining pipeline logic, data behaviour, and architectural decisions.\nMonitor pipeline reliability, data freshness, and system performance; proactively recommend improvements.\nContribute to enhancement and demand assessment by providing technical impact analysis and solution options.\n\n5. Supporting Agile Ways of Working\nBreak down engineering work into clear, testable backlog items that meet the Definition of Ready.\nActively contribute to Agile ceremonies:\nPlanning: provide feasibility, sizing, and technical constraints\nRefinement: structure engineering tasks, clarify implications\nDaily collaboration: support the squad in removing technical blockers\nReviews: showcase engineering increments\nRetrospectives: drive process, quality, and tooling improvements\nPromote iterative delivery, early validation, and continuous learning to increase engineering maturity.\n\n6. Change & Adoption\nProduce high‑quality technical documentation covering pipelines, data models, transformation logic, and operational behaviours.\nSupport deployment, troubleshooting, and onboarding for new data products.\nHelp ensure data products are understood, embedded in workflows, and delivering intended value across breweries and regions.\n\nQualifications\nBachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.\nSignificant experience in data engineering within analytics‑driven or manufacturing/FMCG environments.\nHands‑on experience delivering data platforms, pipelines, and models in Agile product teams.\n\nSkills & Experience\nEssential\nStrong software engineering skills in Python (OOP, packaging, testing frameworks).\nExcellent SQL proficiency and experience with large datasets.\nHandson expertise with AWS and Azure data engineering services (Lambda, Glue, Step Functions, S3, DynamoDB, etc.).\nExperience with Terraform and Infrastructure‑as‑Code practices.\nFamiliarity with CI/CD, Git, and DevOps workflows.\nUnderstanding of ML lifecycle, including model deployment and monitoring.\nAbility to ingest, transform, validate, and structure diverse data sources.\nStrong communication skills and experience in global, cross‑functional product squads.\nFluent English (spoken and written).\nDesirable\nExperience with Spark or distributed data processing frameworks.\nExposure to manufacturing, FMCG, or OT/IT data (MES, SCADA, historian, sensors).\nExperience with BI tools (Power BI, Grafana) and semantic modelling concepts.\nKnowledge of AWS analytics services (Athena, Redshift, SageMaker).\n\nMindset & Behaviours\nAligned with HEINEKEN Behaviours:\nFocus on value — ensuring engineering work drives measurable business outcomes.\nEmpower teams — sharing knowledge openly and contributing to collective success.\nStart quick, learn fast — iterating, validating, and improving continuously.\nContinuously improve — raising engineering quality, performance, and maintainability.\nYou thrive in a squad‑based environment, enjoy solving complex data challenges, and play a key role in enabling smarter, more efficient, and data‑driven breweries.","description_format":"text","description_chars":6501,"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":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Recruiting & Staffing","Freelance & Talent Marketplaces"],"lifecycle":[{"event":"open","at":"2026-11-06T20:10:56Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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