{"id":4228312,"url":"https://alion.io/job/ujjivansfb-lead-data-engineer","title":"Lead Data Engineer","company":{"id":2303231,"name":"Ujjivansfb","domain":"ujjivansfb.in","url":"https://alion.io/company/ujjivansfb","size_band":null,"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":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"Machine Learning","optional":false},{"name":"ETL/ELT","optional":true},{"name":"Git","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"Scala","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-11-13T08:35:50Z","employer_posted_date":null,"last_verified_at":"2026-11-13T08:35:50Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"The Lead Data Engineer will be responsible for architecting, building, and governing enterprise-scale data pipelines and platforms for Ujjivan Small Finance Bank. The role ensures secure, high-quality, reliable, and timely data availability to support analytics, regulatory reporting, risk management, and AI/ML initiatives.\n\nThis role provides technical and people leadership, defines data engineering standards, and acts as a key interface between business, analytics, governance, and technology teams.\n\nSize of the role:\n40+ internal and external data sources across core banking, lending, digital, and credit bureau systems\n150+ automated batch and near-real-time data pipelines processing multi-TB data volumes monthly\nSupports 100+ enterprise dashboards, MIS, and regulatory (RBI/statutory) reports\nData foundation for 25+ analytics and AI/ML use cases across risk, collections, and business\nLeads 7-12 data engineers and manages 3-5 technology vendors while serving 30+ stakeholders\n\nKey duties & responsibilities of the role:\n\nBusiness/ Financials:\nDesign and own end-to-end data pipeline architecture across batch and near real-time processing aligned to enterprise strategy.\nDefine and govern bronze, silver, and gold data layer architecture for enterprise consumption.\nEnable analytics, ML, and AI use cases by delivering model-ready and feature-ready datasets that drive business outcomes.\nOptimize data pipeline performance and cost efficiency.\nEstablish CI/CD pipelines for data engineering, including version control, testing, and controlled deployments.\nContribute to planning, budgeting, and prioritization of data engineering initiatives aligned to business goals.\n\nCustomer (Both Internal & External):\nCollaborate with business, analytics, and risk teams to translate requirements into scalable data solutions.\nLead ingestion of data from Core Banking, LOS, LMS, Collections, CRM, Payments, Finance, and external data sources to support internal and external consumers.\nEnable timely, reliable, and high-quality data availability for stakeholders across the organization.\nPartner with Data Quality & Governance teams to operationalize Critical Data Elements (CDEs), lineage, and metadata for stakeholder trust and usability.\n\nInternal Process:\nEnsure pipeline scalability, fault tolerance, restartability, and SLA adherence.\nImplement workflow orchestration, dependency management, backfills, and automated retries.\nEmbed automated data quality checks, reconciliation controls, and anomaly detection.\nEnsure secure data handling, including masking, encryption, and role-based access control.\nEnsure compliance with regulatory, audit, and information security requirements.\nComply with internal SLAs, policies, and standard operating procedures.\nDrive process management and continuous process excellence across data engineering workflows.\n\nInnovation & Learning:\nUpskill team members to new age technologies with respect to machine learning and credit modelling. Enhance on-job self-learning related to analytics techniques/tools.\nEnsure timely completion of training / learning programs assigned from time to time.\n\nMinimum requirements of knowledge & skills:\n\nEducational Qualifications:\nBachelor's or Master's degree in Engineering, Computer Science, or related field.\n\nExperience Range (Years and Core Experience Type):\n12-15 years of experience in data engineering or large-scale data platform development.\nProven experience in banking or financial services data environments.\nDemonstrated experience leading teams and enterprise data programs.\n\nCertifications:\nNA/ Good to have\n\nFunctional Skills:\nAdvanced SQL and strong programming skills in Python / Scala and PySpark.\nDeep understanding of cloud architecture and DevOps.\nStrong experience with ETL/ELT frameworks and distributed data processing.\nHands-on experience with data orchestration and scheduling frameworks.\nDeep understanding of data warehousing, data lakes, and layered data architectures.\nExpertise in data quality, reconciliation, metadata management, and data lineage.\nStrong knowledge of CI/CD, version control (Git), and automated testing for data pipelines.\nExperience with data security, masking, encryption, and role-based access control.\nExposure to streaming or near real-time data processing is desirable.\nUnderstanding of ML/AI data requirements and feature engineering pipelines.\n\nBehavioral Skills:\nLeadership skills to manage a team of data quality analysts and data engineers.\nExcellent listening, interpersonal, communication, and problem-solving skills.\nDemonstrated ability to work effectively in teams, in both a lead and support role.\nEffective time management skills, including demonstrated ability to manage and prioritize multiple tasks and projects.\nAbility to build strong relationships both internally and externally.\nExceptionally strong organizational, problem-solving, and communication skills.\nStructured thinker, effective communicator with excellent written communication skills.\n\nCompetencies:\nA passion for constantly learning and applying new technologies and programming languages in a constantly evolving environment.\nDemonstrated ability to learn new techniques and troubleshoot code without support.\nPrior people management experience, with tried-and-true approaches for mentoring junior staff.\nUnderstanding of the financial sector, to recognize and drive forward opportunities where data engineering can transform the bank.\nSkilled at influencing and communicating to various stakeholders up to executive level.\n\nKey interactions:\n\nInternal:\nAll Functional Heads (Business & Support functions) and their teams\nDSDM\n\nExternal:\nThird Party Service Providers\nCredit Bureaus\nAuditors\nRegulators\nSkills\nELT, ETL, PySpark, Python, SQL, 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