Data and AI Lead, Finance
Bengaluru, India · 全职 · 职能与运营
需要对标的能力
AI 应用 · 人机协同大模型原理 · LLM 基础Agent · 智能体设计Agent 工程 · Harness / 脚手架权限 · 沙箱 · 治理
岗位职责与要求
GAQ327R175
About the Role
This role is a part of the Finance Organisation.
As Finance Data Lead on the Finance Data and AI team, you will be the technical authority behind the data pipelines, AI systems, and internal applications that power Databricks' Finance and Accounting organisation. You will report to the Senior Manager, Finance Data and AI and serve as the individual contributor who sets the technical bar, drives architectural decisions, and delivers the highest-complexity work on the team. This individual is expected to be based in Bengaluru.
This is a high-impact role at the intersection of finance domain expertise and data platform capability. You will work closely with a team of finance data engineers as a technical lead and mentor, and partner directly with Accounting, FP&A, and Finance leadership to define what gets built and how.
What You Will Do:
· Design and develop ETL pipelines using Databricks SQL and Python / PySpark to enhance reporting, automate journal entries, and transform core financial processes across various domains in accounting and FP&A, such as revenue, expenses, equity, commissions, and tax
· Architect, build, and own the most complex finance data pipelines in the Finance data lake using Databricks Jobs and Lakeflow Declarative Pipelines with built-in data validation and reconciliations
· Lead the technical design of AI use cases for the Finance and Accounting organisation, including forecasting automation, anomaly detection, and natural language interfaces to financial data
· Build and maintain internal Finance applications (Databricks Apps, Genie Agents, AI/BI dashboards) that enable self-service for non-technical Finance stakeholders
· Design and deliver curated Finance datasets and enforce row-level security, data access policies, and Unity Catalog governance standards
· Define and champion coding standards, data modelling conventions, documentation practices, and testing frameworks across the Finance engineering team
· Enforce and evolve Git-based version control, pull-request review processes, and CI/CD pipelines (Declarative Automation Bundles, GitHub Actions) to satisfy SOX change management requirements
· Lead technical scoping and solutioning for requirements from Accounting, FP&A, Internal Audit, and Procurement teams
· Serve as the primary technical point of contact during financial close, ensuring data accuracy and timely resolution of pipeline issues
· Partner with IT and Engineering on new system integrations, providing detailed technical requirements and leading UAT
· Mentor junior and mid-level engineers through code reviews, pairing, and design discussions, raising the technical quality of the broader team
· Proactively identify architectural debt, performance bottlenecks, and tooling gaps, and drive resolution with minimal direction
What We Look For:
· 12+ years of experience in data engineering, analytics engineering, or finance systems, with a track record of owning complex, production-grade pipelines end-to-end
· Deep proficiency in SQL and Python; hands-on experience with Apache Spark and the Databricks platform
· Experience building and maintaining ELT/ETL pipelines from financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar) into a centralised data lake
· Strong understanding of core finance and accounting concepts, including close processes, revenue recognition, intercompany, chart of accounts, and financial reporting
· Ability to independently translate ambiguous Finance requirements into well-architected, maintainable technical solutions
· Comfortable driving technical conversations with both engineering peers and non-technical Finance stakeholders
· Experience building Finance-facing dashboards, self-service BI products, and executive reporting layers
· Familiarity with AI/ML concepts with demonstrated enthusiasm for applying them to Finance workflows
Nice to Have
· Prior experience at a high-growth SaaS or cloud infrastructure company
· Hands-on experience with AI/BI tools, Genie, or LLM-powered applications
· Experience with Declarative Automation Bundles or CI/CD for Finance DataLake pipelines
· CPA, CFA, or formal finance/accounting background
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
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Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
查看中文参考译文
GAQ327R175
关于该职位
该职位隶属于 Finance Organisation。
作为 Finance Data and AI 团队的 Finance Data Lead,你将是支撑 Databricks 的 Finance and Accounting organisation 的数据管道、AI 系统和内部应用的技术权威。你将向 Senior Manager, Finance Data and AI 汇报,并作为 individual contributor 来设定技术标杆、推动架构决策、交付团队内最高复杂度的工作。该岗位预计 base 在 Bengaluru。
这是一个高影响力的职位,处于 finance domain expertise 和 data platform capability 的交汇点。你将作为技术 lead 和 mentor,与 finance data engineers 团队紧密合作,并直接与 Accounting、FP&A 和 Finance leadership 协作,定义要构建什么以及如何构建。
你将做什么:
· 使用 Databricks SQL 和 Python / PySpark 设计和开发 ETL pipelines,以提升 reporting、自动化 journal entries,并 transform core financial processes,涵盖 accounting 和 FP&A 的多个领域,如 revenue、expenses、equity、commissions 和 tax
· 在 Finance data lake 中,使用 Databricks Jobs 和 Lakeflow Declarative Pipelines 架构、构建并 owning 最复杂的 finance data pipelines,内置 data validation 和 reconciliations
· 为 Finance and Accounting organisation 的 AI use cases 进行技术设计,包括 forecasting automation、anomaly detection,以及面向 financial data 的 natural language interfaces
· 构建和维护内部 Finance applications(Databricks Apps、Genie Agents、AI/BI dashboards),为非技术背景的 Finance stakeholders 提供 self-service
· 设计并交付 curated Finance datasets,并 enforce row-level security、data access policies 和 Unity Catalog governance standards
· 在 Finance engineering team 中定义并推行 coding standards、data modelling conventions、documentation practices 和 testing frameworks
· 执行并演进 Git-based version control、pull-request review processes 和 CI/CD pipelines(Declarative Automation Bundles、GitHub Actions),以满足 SOX change management requirements
· 为来自 Accounting、FP&A、Internal Audit 和 Procurement teams 的需求进行技术 scoping 和 solutioning
· 在 financial close 期间担任主要技术 contact point,确保 data accuracy 和 pipeline issues 的及时解决
· 与 IT 和 Engineering 合作推进 new system integrations,提供详细的技术需求并主导 UAT
· 通过 code reviews、pairing 和 design discussions 指导 junior 和 mid-level engineers,提升整个团队的技术质量
· 主动识别 architectural debt、performance bottlenecks 和 tooling gaps,并在 minimal direction 的情况下推动解决
我们寻找什么:
· 12 年以上 data engineering、analytics engineering 或 finance systems 经验,有 owning complex, production-grade pipelines end-to-end 的 track record
· 精通 SQL 和 Python;有 Apache Spark 和 Databricks platform 的实操经验
· 有从 financial source systems(NetSuite、Salesforce、Stripe、Zuora 或类似系统)构建和维护 ELT/ETL pipelines 到 centralised data lake 的经验
· 对 core finance and accounting concepts 有深入理解,包括 close processes、revenue recognition、intercompany、chart of accounts 和 financial reporting
· 能够独立将模糊的 Finance requirements 转化为架构良好、可维护的技术方案
· 能够自如地与 engineering peers 和非技术背景的 Finance stakeholders 进行技术对话
· 有构建 Finance-facing dashboards、self-service BI products 和 executive reporting layers 的经验
· 熟悉 AI/ML concepts,并对将其应用于 Finance workflows 有 demonstrated enthusiasm
加分项
· 有 high-growth SaaS 或 cloud infrastructure company 的工作经验
· 有 AI/BI tools、Genie 或 LLM-powered applications 的实操经验
· 有 Declarative Automation Bundles 或 Finance DataLake pipelines 的 CI/CD 经验
· CPA、CFA 或正式的 finance/accounting 背景
关于 Databricks
Databricks 是数据与 AI 公司。全球超过 10,000 家组织——包括 Comcast、Condé Nast、Grammarly 以及超过 50% 的 Fortune 500 企业——依赖 Databricks Data Intelligence Platform 来统一和 democratize 数据、analytics 和 AI。Databricks 总部位于 San Francisco,在全球设有办公室,由 Lakehouse、Apache Spark™、Delta Lake 和 MLflow 的原创作者创立。欲了解更多信息,请在 Twitter、LinkedIn 和 Facebook 上关注 Databricks。
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如果履行工作职责需要访问 export-controlled technology 或 source code,是否申请 U.S. government license 由 Employer 自行决定,Employer 可仅基于此理由拒绝继续推进该 applicant。
译文仅供辅助阅读,具体要求以原始招聘来源为准。