Senior Data Engineer, Finance

Reposted Yesterday
3 Locations
Remote
162K-284K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software
The Role
Lead migration of financial data pipelines from Snowflake to AWS, design SOX-compliant dimensional models, build Medallion Architecture datasets, implement data quality, observability, CI/CD, and performance optimizations, and partner with stakeholders to deliver production-ready financial analytics at scale.
Summary Generated by Built In

Be the one building AI-powered experiences where they matter most.


At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.


Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.


*Note this role is remote for candidates residing in US within EST or CST time zone (Central to East Cost only).


Role Overview:

This role shapes the future of financial data at scale by transforming how critical business data is modeled, governed, and delivered across the organization. You will lead the evolution of a modern data platform, migrating complex pipelines into AWS while ensuring auditability, performance, and trust for financial reporting. At Genesys, we are redefining how organizations engage with customers through AI-driven experiences, and this role directly supports that mission by enabling accurate, timely, and reliable data for strategic decision-making. You will operate with high autonomy, influencing architecture, engineering standards, and cross-functional data strategy across Finance and Customer Success. This position offers visibility into enterprise initiatives and the opportunity to drive platform-level impact while expanding technical and leadership capabilities.


This position is not eligible for employer-sponsored work authorization (e.g., H-1B, TN, O-1, or other employment-based visas), now or in the future. Applicants must be legally authorized to work in the United States at the time of application and throughout employment without the need for current or future employer sponsorship.


Key Responsibilities:


  • Own the end-to-end migration of data pipelines from Snowflake to AWS, improving scalability, cost efficiency, and system observability
  • Design and implement dimensional data models that enable accurate, SOX-compliant financial reporting and analytics
  • Build and evolve Medallion Architecture data layers, ensuring high-quality, testable Silver and Gold datasets
  • Drive performance optimization across SQL transformations and data processing workflows to reduce cost and improve execution efficiency
  • Establish and enforce engineering standards for testing, deployment, and documentation across data platforms
  • Implement data quality frameworks that improve data reliability through validation, anomaly detection, and monitoring
  • Lead architecture decisions and influence technical direction across Strategic Finance and Customer Success data ecosystems
  • Partner with business stakeholders to translate complex requirements into scalable, production-ready data solutions

Required Qualifications:


  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
  • 6+ years of experience building production-grade data platforms or modern data warehouse solutions
  • Expert-level SQL skills, including complex query design, performance tuning, and large-scale data modeling
  • Strong Python development experience for building robust data pipelines and automation
  • Proven experience working with cloud-based data platforms, including Snowflake and AWS services
  • Demonstrated expertise in CI/CD pipelines, Git-based workflows, and automated testing frameworks
  • Strong understanding of data governance, observability, and monitoring best practices
  • Ability to communicate complex technical concepts effectively to both technical and business stakeholders
  • Familiarity with AWS services such as Glue, S3, and CloudWatch for data pipeline orchestration

Preferred Qualifications:


  • Experience designing and implementing financial data models in regulated environments
  • Experience with data lineage, cataloging tools, and enterprise data governance frameworks
  • Track record of leading cross-functional data initiatives with measurable business impact

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.  

$161,500.00 - $283,900.00

Benefits:

  • Medical, Dental, and Vision Insurance. 

  • Telehealth coverage

  • Flexible work schedules and work from home opportunities

  • Development and career growth opportunities

  • Open Time Off in addition to 10 paid holidays

  • 401(k) matching program

  • Adoption Assistance

  • Fertility treatments

Click here to view a summary overview of our Benefits.


Working at Genesys

  • AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year.
  • A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
  • Growth in the AI era – Build future-ready skills through mentorship, learning programs, leadership development and education support.
  • Time to recharge and give back – Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families.
  • Recognized globally – Genesys is Great Place to Work® certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.

Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.


What Happens After You Apply

After you apply, here's what you can typically expect:

  • Our Talent Acquisition team reviews your application with the hiring team.
  • A Talent Acquisition Partner will review your application and, if your background is aligned, schedule a Zoom interview.

  • Next, you'll meet the hiring manager and other members of the interview team.
  • We aim to keep the process focused and respectful of your time, with no more than five interviews in most cases.
  • After interviews are complete, our team will follow up with the final steps.

Every application is reviewed by a person. Response times may vary by role and location, but our team will keep you informed throughout the process.


Stay Connected

Stay connected to learn more about how we're applying AI to customer and employee experience challenges and get notified when relevant opportunities become available.

Get notified about relevant opportunities.


Be the one building what's next - where AI, experience and impact come together.

Employee Referral

If a Genesys employee referred you, please apply using the link they shared so we can connect your application to their referral.


About Genesys:

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. Genesys Cloud™ is the Agentic Orchestration Platform that securely connects people, systems, data and AI across the enterprise with built-in governance and control. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.ai. 

Reasonable Accommodations:

If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at [email protected].


You can expect a response within 24–48 hours. To help us provide the best support, click the email link above to open a pre-filled message and complete the requested information before sending. If you have any questions, please include them in your email.

 

This email is intended to support job seekers requesting accommodations. Messages unrelated to accommodation—such as application follow-ups or resume submissions—may not receive a response.


Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.


Please note that recruiters will never ask for sensitive personal or financial information during the application phase.

Skills Required

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field or equivalent experience
  • 6+ years experience building production-grade data platforms or modern data warehouse solutions
  • Expert-level SQL skills including complex query design, performance tuning, and large-scale data modeling
  • Strong Python development experience for building data pipelines and automation
  • Proven experience with cloud-based data platforms, including Snowflake and AWS services
  • Familiarity with AWS services such as Glue, S3, and CloudWatch for data pipeline orchestration
  • Demonstrated expertise in CI/CD pipelines, Git-based workflows, and automated testing frameworks
  • Strong understanding of data governance, observability, and monitoring best practices
  • Ability to communicate complex technical concepts effectively to both technical and business stakeholders
  • Experience owning end-to-end migration of data pipelines (Snowflake to AWS) and optimizing SQL/data processing for performance and cost
  • Design and implement dimensional data models that support SOX-compliant financial reporting and analytics
  • Experience designing and implementing financial data models in regulated environments
  • Experience with data lineage, cataloging tools, and enterprise data governance frameworks
  • Track record of leading cross-functional data initiatives with measurable business impact

Genesys Compensation & Benefits Highlights

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

  • Strong & Reliable Incentives Annual bonuses are described as consistently funded and meaningful, elevating total compensation. Structured variable pay and regular payouts reinforce confidence in incentives across numerous roles.
  • Leave & Time Off Breadth Open (unlimited) PTO, volunteer time off, and company recharge days create flexible time-away options. Remote-friendly policies and occasional holiday shutdowns add to the sense of generous time off.
  • Parental & Family Support Paid parental leave with no waiting period, fertility support, and adoption assistance signal strong family-oriented benefits. These offerings stand out as modern and comprehensive within the package.

Genesys Insights

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The Company
HQ: Menlo Park, CA
6,774 Employees
Year Founded: 1990

What We Do

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. Genesys Cloud™ is the Agentic Orchestration Platform that securely connects people, systems, data and AI across the enterprise with built-in governance and control. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.ai.

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