{"id":2337344,"url":"https://alion.io/job/rakuten-lead-data-engineer","title":"Lead Data Engineer","company":{"id":13251,"name":"Rakuten","domain":"rakuten.co.in","url":"https://alion.io/company/rakuten","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Keras","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLTK","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-12T10:13:46Z","employer_posted_date":null,"last_verified_at":"2026-10-12T10:13:46Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Responsibilities:\nWork cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.\nDevelop scalable algorithms and methods to provide real-time recommendations.\nExplore new technology shifts to determine how they might connect with the customer benefits we wish to deliver.\nWork with engineering teams to implement new models while considering functionality for recommendation output.\nCollaborate with data scientists to prototype new algorithms and design experiments for evaluation to enhance our marketing efficiency.\nContribute to a culture of continuous improvement and data-driven results.\nWork with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.\nRun regular A/B tests, gather data, perform statistical analysis, and draw conclusions on the impact of your models.\nDiscover data sources and ingest and cleanse them in a meaningful way for data processing.\nParticipate in design discussions about new features and approaches to implementing new services.\nTake end-to-end ownership of machine learning systems, from data pipelines and training to real-time prediction engines.\nPartner with data scientists to understand, implement, refine, and design machine learning and other algorithms.\nRequirements:\nBachelor's degree or higher (completed and verified before start) from an accredited university.\nPreferably working experience in the FinTech or credit card industry.\nKnowledgeable with data science tools and frameworks (i. e., Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, and Spark).\nSoftware engineering fundamentals: version control systems (i. e., Git, Github) and workflows, and ability to write production-ready code.\nShould have a clear understanding of generative AI and various LLM models.\nDatabricks Delta Lake architecture and MLflow are added advantages.\nGood knowledge of Azure cloud infrastructure.\nStrong knowledge of machine learning techniques (i. e., classification, regression, and clustering).\nBS, MS, or PhD degree in computer science or a related field, or equivalent practical experience.\nUnderstand machine learning principles (training, validation, etc. ).\nExpertise in visualizing and manipulating big datasets.\nKnowledge of data query and data processing tools (i. e., SQL).","description_format":"text","description_chars":2362,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Marketplaces","Consumer Internet Groups"],"lifecycle":[{"event":"open","at":"2026-10-12T10:13:46Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 15 · green card filings: 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