{"id":1252078,"url":"https://alion.io/job/standard-chartered-lead-ai-data-engineer","title":"Lead AI Data Engineer","company":{"id":20709,"name":"Standard Chartered","domain":"sc.com","url":"https://alion.io/company/standard-chartered-gbs","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","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":["China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":35000,"max_usd":76000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":328},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache Pulsar","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"Machine Learning","optional":false},{"name":"MinIO","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Unstructured.io","optional":false}],"status":"live","first_seen_at":"2026-09-25T18:36:02Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-26T02:18:31Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\nA senior data engineer who builds the pipelines and data infrastructure that feed AI/ML and agentic applications, owning ingestion through to retrieval-ready, feature-ready data.\nKey Responsibilities\nMust-have\nProduction data pipelines at scale. You've built and operated batch and/or streaming pipelines that other teams depend on, and owned them through schema changes, backfills, and on-call.\nSpark and Databricks (or equivalent distributed compute). Comfortable tuning jobs for skew, shuffle, partitioning, and memory under real workloads, and working within a lakehouse platform like Databricks (Delta, Unity Catalog, workflows).\nObject stores as the data backbone. S3 / ADLS / MinIO, with strong grasp of partitioning, file formats (Parquet / Delta / Iceberg), compaction, and the cost and performance tradeoffs that come with them.\nData integration across heterogeneous sources. Databases, APIs, event streams, and files stitched into reliable, coherent flows. This is the core of the role.\nUnstructured data. Parsing, chunking, and normalizing documents and multimodal content into something AI systems can actually consume.\nSystem design. You reason clearly about throughput, latency, consistency, idempotency, and cost, and can defend your decisions.\nStrongly preferred\nFeature engineering for ML, building and serving features with offline/online consistency.\nStreaming and big-data stack, including Kafka / Kinesis / Pulsar, Flink, and lakehouse patterns.\nOpen-source contributions, a signal of depth beyond day-job delivery.\nCoach and mentor our team as we build scalable machine learning solutions\nStrong communication skills and an easy-going attitude\nBuild and manage strong relationships with stakeholders and various teams internally and externally\nYou'll pick up on the job (preferred, not required)\nRAG pipelines, including embedding generation, vector stores, and retrieval quality.\nAgentic integrations, the tool and data interfaces for autonomous AI workflows.\nStrategy\nAs the Squad member of AI team, the candidate is expected to participate and drive deliverables associated with Business Use cases.\nBusiness\nUnderstand the Business requirement and execute the solutioning and ensue the delivery commitments are delivered on time and schedule.\nProcesses\nDesign and Delivery of AI ML Use cases\nRAI, Security & Governance\nModel Validation & Improvements\nStakeholder Management\nPeople & Talent\nManage the team in terms of project assignments and deadlines\nManage a team dedicated for reviewing models related unstructured and structured data.\nHire, nurture talent as required.\nRisk Management\nOwnership of the delivery, highlighting various risks on a timely manner to the stakeholders.\nIdentifying proper remediation plan for the risks with proper risk roadmap.\nGovernance\nAwareness and understanding of the regulatory framework, in which the Group operates, and the regulatory requirements and expectations relevant to the role.\nRegulatory & Business Conduct\nDisplay exemplary conduct and live by the Group’s Values and Code of Conduct.\nTake personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.\nEffectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.\nKey Stakeholders\nBusiness Stakeholders\nAIML Engineering Team\nAIML Product Team\nProduct Enablement Team\nSCB Infrastructure Team\nInterfacing Program Team\nSkills and Experience\nBuild and maintain pipelines using Python, SQL, Spark\nWrite ETL/ELT ingestion into Delta Lake or Iceberg tables\nImplement data quality checks and route failures\nWork with cloud storage and compute (ADLS, S3, Spark)\nPrepare feature-ready datasets for ML and embedding pipelines\nSupport data warehouse and data lake environments\nWork with AI platform and data science teams on data needs\nSQL\nPython\nETL and ML concepts\nApache Spark\nAzure/AWS fundamentals\nDatawarehouse\nDatalake knowledge\nDistributed systems design, and architecture.\nGood to have: Flink, Vector\nQualifications\nMasters with specialisation in Technology with certification in AI and ML\n6-10 years relevant of Hands-on Experience in developing and delivering AI solutions\nAbout Standard Chartered\nWe're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us.\nOur purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion.\nTogether we:\nDo the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do\nNever settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well\nAre better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term\nWhat we offer\nIn line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.\nCore bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.\n Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.\nFlexible working options based around home and office locations, with flexible working patterns.\nProactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits\nA continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.\n Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.","description_format":"text","description_chars":6904,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Annual leave","Continuous learning","Flexible schedule","Life insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Wealth Management & Financial Advisors","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-09-25T18:36:02Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":35,"reasons":["conf:3","win:early","comp:brand"],"computed_at":"2026-09-26T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/standard-chartered-lead-ai-data-engineer","json_url":"https://alion.io/job/standard-chartered-lead-ai-data-engineer.json","meta":{"generated_at":"2026-09-27T04:53:11Z","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":4273,"day_limit":5000,"remaining_today":727,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}