AVP – Data Engineer / Analytics Engineer

Posted 9 Hours Ago
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Hiring Remotely in Hong Kong
Remote
Mid level
Financial Services
The Role
Build and maintain Snowflake-based transformation pipelines to produce governed, analytics-ready fact and dimension tables. Enforce data quality, performance tuning, and access controls. Automate workflows (Airflow, Snowflake Tasks, TWS), monitor pipelines, collaborate with finance and analytics stakeholders, and support downstream consumers.
Summary Generated by Built In

Role Overview

We are looking for a Data Engineer/Analytics Engineer to join a cross‑functional technology team responsible for building and maintaining modern financial data platforms. This role focuses on the design and delivery of reliable data transformation layers that support sub‑ledger reporting, reconciliation, and downstream analytics.

The role is hands‑on and execution‑focused, working on Snowflake and Sigma to transform transactional data into governed, analytics‑ready models. You will collaborate closely with finance, product control, engineering, and analytics partners to ensure data accuracy, transparency, and usability.

This is an ideal role for an engineer early in their finance‑data journey who wants to develop strong foundations in financial data modeling, controls, and modern cloud tooling.


Key Responsibilities

  • Build and maintain modular modules and transformation pipeline in Snowflake to support sub‑ledger and financial reporting use cases.
  • Work closely with analysts, finance partners, and engineers to understand requirements.
  • Develop transformation logic to convert raw transactional data into clean, well‑structured fact and dimension tables.
  • Enforce data quality through rigorous testing, documentation, and version control following DevOps processes.
  • Participate in Agile ceremonies (e.g., stand-ups, sprint planning) and manage tasks using Jira.
  • Optimize Snowflake performance (Clustering, Warehouses, Query tuning).
  • Implement and follow data access controls and security practices for regulated financial data.
  • Help automate workflows using Airflow, Snowflake Tasks or TWS.
  • Monitor pipeline executions, investigate failures, and support issue resolution.
  • Support end users and downstream data consumers 

Mandatory Qualifications & Skills

  • 3–5 years of experience in data engineering or analytics engineering roles.
  • Hands‑on experience working with Snowflake as a cloud data warehouse.
  • Strong proficiency in SQL and understanding of dimensional data modeling concepts.
  • Working knowledge of Python for pipeline integration or orchestration tasks.
  • Familiarity with Git‑based version control and DevOps practices.
  • Ability to work effectively with both technical and finance stakeholders.
  • Experience working in Agile/Scrum environments.
  • Experience with Analytics/BI tools such as Sigma or Qlik is a huge plus.

Nice‑to‑Have Skills

  • Exposure to financial or sub‑ledger datasets (trades, positions, balances, movements).
  • Familiarity with data vault and modeling concepts
  • Understanding of MCP and AI Agents.

Education & Experience

  • Bachelor’s degree in Computer Science, Data Engineering, Finance Technology, or a related field.
  • Prior experience working in cross‑functional teams involving engineers, analysts, and business users.
  • Strong attention to detail, willingness to learn, and a focus on data accuracy and reliability.
About Us

Jefferies is a leading global, full-service investment banking and capital markets firm that provides advisory, sales and trading, research, and wealth and asset management services. With more than 40 offices around the world, we offer insights and expertise to investors, companies, and governments.

At Jefferies, we believe that diversity fosters creativity, innovation and thought leadership through the infusion of new ideas and perspectives. We have made a commitment to building a culture that provides opportunities for all employees regardless of our differences and supports a workforce that is reflective of the communities where we work and live. As a result, we are able to pool our collective insights and intelligence to provide fresh and innovative thinking for our clients.

Jefferies is an equal employment opportunity employer, and takes affirmative action to ensure that all qualified applicants will receive consideration for employment without regard to race, creed, color, national origin, ancestry, religion, gender, pregnancy, age, physical or mental disability, marital status, sexual orientation, gender identity or expression, veteran or military status, genetic information, reproductive health decisions, or any other factor protected by applicable law. We are committed to hiring the most qualified applicants and complying with all federal, state, and local equal employment opportunity laws. As part of this commitment, Jefferies will extend reasonable accommodations to individuals with disabilities, as required by applicable law.

Skills Required

  • 3-5 years of data engineering or analytics engineering experience
  • Hands-on experience with Snowflake
  • Strong proficiency in SQL
  • Working knowledge of Python
  • Familiarity with Git-based version control
  • Experience with DevOps practices
  • Experience working in Agile/Scrum environments
  • Experience collaborating with finance and analytics stakeholders
  • Familiarity with Jira for task management
  • Experience automating workflows using Airflow, Snowflake Tasks, or TWS
  • Experience with Analytics/BI tools such as Sigma or Qlik
  • Bachelor's degree in Computer Science, Data Engineering, Finance Technology, or related field
  • Exposure to financial or sub-ledger datasets (trades, positions, balances)
  • Familiarity with data vault and modeling concepts
  • Understanding of MCP and AI Agents

Jefferies Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Jefferies and has not been reviewed or approved by Jefferies.

  • Strong & Reliable Incentives Compensation is positioned as competitive with meaningful upside, with potential for significant earnings depending on group performance and strong years. A formulaic, performance-linked bonus model ties payouts to individual fees or P&L, reinforcing a pay-for-results dynamic.
  • Parental & Family Support Family-building support is broad, including primary and non-primary caregiver leave, adoption assistance, subsidized emergency child and eldercare, and a $25,000 stipend for qualified surrogacy, adoption, or fertility support. Added resources like family support programs and parental-leave coaching further strengthen caregiver benefits.
  • Wellbeing & Lifestyle Benefits Lifestyle perks extend beyond standard coverage, including discount programs, commuter benefits, legal plans, charitable matching, and education assistance such as tuition support and scholarships for employees’ family members. Location-specific perks like gym stipends and free cafeteria lunch are also described as available in some offices.

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The Company
HQ: New York, NY
6,435 Employees
Year Founded: 1962

What We Do

Jefferies, the global investment banking firm, has served companies and investors for 60 years. Headquartered in New York, with offices in over 30 cities around the world, the firm provides clients with capital markets and financial advisory services, institutional brokerage and securities research, as well as asset and wealth management. The firm provides research and execution services in equity, fixed income, and foreign exchange markets, as well as a full range of investment banking services including underwriting, mergers and acquisitions, restructuring and recapitalization, and other advisory services, with all businesses operating in the Americas, Europe and Asia. Jefferies Group LLC is a wholly-owned subsidiary of Jefferies Financial Group (NYSE: JEF), a diversified financial services company. More about our company can be found at www.jefferies.com.

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