Data Engineer Jobs in USA with Visa Sponsorship
Data engineer roles carry strong sponsorship potential due to their technical depth in building and maintaining large-scale data pipelines, ETL systems, and cloud infrastructure. Employers view data engineers similarly to software engineers when evaluating sponsorship decisions, and proficiency in platforms like AWS, GCP, Snowflake, and Spark significantly strengthens candidacy. STEM degree holders benefit from the 36-month OPT extension while pursuing long-term H-1B sponsorship. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.
ABOUT THE ROLE
Replit is redefining how software is built, and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we are building a brand that is as iconic, inventive, and human as the product itself. We need a Financial Systems Data Engineer to build the data infrastructure that ensures we can accurately recognize revenue, reconcile payments, pass audits, and make sound financial decisions as we scale. This Data team role works cross-functionally with Finance, Accounting, and Sales to build the systems they depend on. You'll own the data models and pipelines that power financial reporting, billing reconciliation, and revenue operations. This is a building role, we need someone who can own the financial data domain end-to-end.
YOU WILL
- Build unified data models for payments and subscriptions across all revenue streams (Stripe, App Store, Play Store) to enable accurate MRR analysis, revenue recognition, and financial reporting.
- Design automated reconciliation pipelines and audit trails that surface payment discrepancies and data quality issues before they impact month-end close or financial audits.
- Create foundational billing infrastructure for AI agent usage and consumption products, managing the end-to-end flow from metering to revenue recognition while partnering with Engineering, Finance, and Sales Operations.
REQUIRED SKILLS AND EXPERIENCE
- 7+ years in data engineering with significant exposure to financial and payments data
- Deep experience with Stripe or similar billing data models—you understand the relationship between subscriptions, invoices, payment intents, charges, and balance transactions
- Strong understanding of SaaS financial metrics (ARR, MRR, churn, expansion) and how they're calculated from raw payment data
- Experience building reconciliation pipelines and automated discrepancy detection
- Expert-level SQL and dbt proficiency—you'll own financial data models end-to-end
- Track record working directly with Accounting and Finance teams on data accuracy requirements
- Experience operating in ambiguous environments where you define the requirements, not just execute them
PREFERRED QUALIFICATIONS
- Understanding of revenue recognition principles (ASC 606 basics)
- Experience with mobile app store financial reporting (App Store Connect, Google Play Console)
- Familiarity with usage-based and consumption billing models
- Experience preparing data infrastructure for audits (SOC 2, financial audits)
- Exposure to billing/subscription, tax and payments management systems (Orb, Chargebee, Recurly, or similar)
BONUS POINTS
- You understand that "close enough" isn't acceptable for financial data—pennies matter
- You've debugged payment discrepancies and know the satisfaction of finding the root cause
- You've built data infrastructure from scratch, not just maintained existing systems
- You're comfortable making decisions with incomplete information and adjusting as you learn
- You treat data quality issues as engineering problems to solve, not business problems to escalate
- You've identified and solved problems no one asked you to solve
LOCATION
This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday.
FULL-TIME EMPLOYEE BENEFITS INCLUDE
- Competitive Salary & Equity
- 401(k) Program with a 4% match
- ⚕️ Health, Dental, Vision and Life Insurance
- Short Term and Long Term Disability
- Paid Parental, Medical, Caregiver Leave
- Commuter Benefits
- Monthly Wellness Stipend
- Autonomous Work Environment
- In Office Set-Up Reimbursement
- Flexible Time Off (FTO) + Holidays
- Quarterly Team Gatherings
- ☕ In Office Amenities
WANT TO LEARN MORE ABOUT WHAT WE ARE UP TO?
- Meet the Replit Agent
- Replit: Make an app for that
- Replit Blog
- Amjad TED Talk
INTERVIEWING + CULTURE AT REPLIT
- Operating Principles
- Reasons not to work at Replit
To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.
How to Get Visa Sponsorship as a Data Engineer
Leverage data engineering's strong specialty occupation fit
Data engineering roles require deep knowledge of distributed systems, database architecture, and programming - a clear match for H-1B specialty occupation requirements. Job descriptions for this role rarely face the ambiguity challenges that more general analyst titles do.
Earn cloud data platform certifications
Snowflake SnowPro Core, Databricks Certified Data Engineer, and AWS Data Analytics Specialty certifications validate your expertise. They signal to employers that you can hit the ground running on their data stack.
Target companies building modern data platforms
Every company with significant data needs pipeline engineers. Snowflake, Databricks, dbt Labs, and Confluent are building the data tools themselves and sponsor H-1B petitions for engineers who understand the technology deeply.
Use STEM OPT to master your company's data stack
A STEM-eligible degree gives you up to 3 years of work authorization through OPT. Data pipelines are complex and company-specific - employers are more likely to sponsor someone who already knows their Airflow DAGs and Spark jobs.
Highlight the engineering depth of your role
Data engineering sits firmly on the software engineering side of the data spectrum. Emphasize skills in Spark, Airflow, dbt, and cloud infrastructure to distinguish your role from more general data positions when filing under SOC 15-1252.
Explore cap-exempt data infrastructure roles
University research computing teams and national labs process massive datasets and need data engineers to build the pipelines. These positions are H-1B cap-exempt - no lottery required and filing is open year-round.
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Get Access To All JobsFrequently Asked Questions
Is it easier to get visa sponsorship as a data engineer compared to a data scientist?
Data engineers and data scientists have comparable sponsorship strength, but the pathways differ slightly. Data engineer roles are closer to software engineering in scope, which gives them strong specialty occupation standing with USCIS. Data scientist roles often require advanced degrees, which provides an advantage through the H-1B master's cap exemption. Both are highly sponsorable, but data engineers may have an edge at companies with larger infrastructure needs.
Do cloud certifications like AWS or GCP help with H-1B approval for data engineers?
Cloud certifications do not directly affect H-1B approval, as the visa requires a bachelor's degree rather than certifications. However, they strengthen the overall petition by providing additional evidence that the role demands specialized technical knowledge. They also make you more competitive in the hiring process, which indirectly improves sponsorship chances by demonstrating alignment between your skills and the position's requirements.
Which industries sponsor data engineers most actively?
Technology companies are the largest sponsors, but financial services, healthcare, and e-commerce are close behind. Any company investing heavily in real-time analytics, data lakes, or ML infrastructure needs data engineers to build and maintain that foundation. Fintech companies and large banks are particularly active sponsors because their data pipelines are business-critical and require specialized expertise in distributed systems and regulatory data handling.
Do data engineers need a computer science degree specifically for visa sponsorship?
A computer science degree is the most common path, but degrees in information systems, software engineering, mathematics, or electrical engineering also qualify. The key is that the employer's job description lists your degree field among the qualifying fields for the position. USCIS evaluates whether your specific degree relates to the job duties, so a degree in statistics or applied math combined with strong technical experience in data pipeline development can work well.
What technical skills should I highlight in a data engineer visa petition?
Proficiency in SQL, Python, and distributed computing frameworks like Spark or Kafka are foundational. Experience with cloud data platforms (AWS Redshift, Google BigQuery, Snowflake) and data orchestration tools (Airflow, dbt, Dagster) demonstrates the specialized technical depth USCIS looks for. Listing these specific technologies in the petition documentation helps distinguish the role from general software development and strengthens the specialty occupation case.
What is the prevailing wage requirement for sponsored Data Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage", the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level. For example, a data engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search Page.
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