Data Science Manager Jobs at Intuit with Visa Sponsorship
Data Science Manager jobs at Intuit sit at the intersection of product analytics, machine learning, and financial technology, leading teams that power products used by millions. Intuit has a consistent track record of sponsoring work visas for this function across multiple visa categories.
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About the Team
The teams own the end-to-end data path at Credit Karma — from service emission to datalake landing to consumer hydration. We build the frameworks, pipelines, and persistence layers that every product team depends on to move data reliably at scale. Our systems ingest hundreds of terabytes per day across Kafka, Pub/Sub, and Dataflow, persist to Spanner and BigQuery, and serve low-latency reads to real-time product experiences through our Unified Consumer Profile (UCP) platform.
This is a foundational engineering role — you will build the frameworks and infrastructure that other engineers across Credit Karma use to ship data-intensive features. If you care about developer experience, system reliability, and solving hard distributed systems problems at scale, this team is for you.
- Design, build, and maintain high-throughput, low-latency data frameworks used across Credit Karma's engineering organization, including ETL templates, persistence libraries, and streaming data pipelines
- Develop and extend Scala-based microservices and frameworks built on Finagle, Akka Streams, and gRPC that process petabytes of data daily
- Build and optimize cloud-native data pipelines on Google Cloud Platform using Dataflow (Apache Beam), Pub/Sub, BigQuery, and Spanner
- Own and evolve our Kafka-based streaming infrastructure — designing producers, consumers, and connectors that handle hundreds of terabytes of events per day with strict latency and durability guarantees
- Build persistence frameworks that provide a unified, type-safe API for reading and writing across Spanner, MySQL, and BigQuery
- Design and implement encryption, decryption, and fine-grained access control capabilities as reusable framework features, ensuring compliance with data governance requirements
- Create self-service developer tooling — CLI tools, templates, and onboarding automation — that reduces the time for other teams to adopt the data platform from weeks to hours
- Drive technical design through architecture reviews and Technical Design Documents (TDDs), influencing decisions across the broader Data & AI organization
- Participate in on-call rotations and build observability (dashboards, alerting, metrics) into every system you ship
What's Great About the Role
- You will own foundational infrastructure — the frameworks you build are the building blocks that every data pipeline and product feature at Credit Karma depends on
- You will work at real scale — hundreds of terabytes per day, millions of consumer profiles hydrated in real time, and strict SLAs that demand engineering rigor
- You will shape developer experience — designing the APIs, SDKs, and tooling that hundreds of engineers across the company interact with daily
- You will solve hard, novel problems — from building MySQL CDC pipelines with cloud-native encryption to designing Apache Beam framework SDKs that support both Java and Python
- You will be part of a high-impact, collaborative team with a strong culture of technical ownership and continuous learning
Minimum Basic Requirements
- 7+ years of professional software engineering experience building backend services and data infrastructure in Scala, Java, or a similar JVM language
- 7+ years of experience designing and operating high-throughput, low-latency distributed systems that process data at petabyte scale
- 3+ years of experience with streaming and messaging platforms such as Apache Kafka, Google Pub/Sub, or equivalent
- 3+ years of experience building data pipelines on a major cloud platform (GCP, AWS, or Azure), including services like Dataflow, BigQuery, Spanner, or their equivalents
- Professional experience with RPC frameworks such as Finagle, gRPC, or Akka for building production-grade service-to-service communication
- Strong understanding of software engineering best practices including CI/CD, version control (Git), code review, and automated testing
Qualifications
Preferred Qualifications
- Experience building reusable frameworks, SDKs, or platform libraries consumed by other engineering teams — you think about developer experience as a product
- Experience with Apache Beam (Dataflow) including custom transforms, side inputs, windowing strategies, and pipeline optimization
- Experience with Change Data Capture (CDC) patterns, particularly MySQL binlog-based replication to analytical stores
- Experience with data encryption at rest and in transit, including key management (KMS/GSM), SPIFFE/mTLS, and certificate authority integration
- Experience with schema management, data governance, and data quality frameworks in a large-scale production environment
- Familiarity with infrastructure-as-code, Kubernetes (GKE), and container-based deployment models
- Track record of mentoring engineers and driving technical alignment across teams through design documents and architecture reviews
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
Overview
About the Team
The teams own the end-to-end data path at Credit Karma — from service emission to datalake landing to consumer hydration. We build the frameworks, pipelines, and persistence layers that every product team depends on to move data reliably at scale. Our systems ingest hundreds of terabytes per day across Kafka, Pub/Sub, and Dataflow, persist to Spanner and BigQuery, and serve low-latency reads to real-time product experiences through our Unified Consumer Profile (UCP) platform.
This is a foundational engineering role — you will build the frameworks and infrastructure that other engineers across Credit Karma use to ship data-intensive features. If you care about developer experience, system reliability, and solving hard distributed systems problems at scale, this team is for you.
- Design, build, and maintain high-throughput, low-latency data frameworks used across Credit Karma's engineering organization, including ETL templates, persistence libraries, and streaming data pipelines
- Develop and extend Scala-based microservices and frameworks built on Finagle, Akka Streams, and gRPC that process petabytes of data daily
- Build and optimize cloud-native data pipelines on Google Cloud Platform using Dataflow (Apache Beam), Pub/Sub, BigQuery, and Spanner
- Own and evolve our Kafka-based streaming infrastructure — designing producers, consumers, and connectors that handle hundreds of terabytes of events per day with strict latency and durability guarantees
- Build persistence frameworks that provide a unified, type-safe API for reading and writing across Spanner, MySQL, and BigQuery
- Design and implement encryption, decryption, and fine-grained access control capabilities as reusable framework features, ensuring compliance with data governance requirements
- Create self-service developer tooling — CLI tools, templates, and onboarding automation — that reduces the time for other teams to adopt the data platform from weeks to hours
- Drive technical design through architecture reviews and Technical Design Documents (TDDs), influencing decisions across the broader Data & AI organization
- Participate in on-call rotations and build observability (dashboards, alerting, metrics) into every system you ship
What's Great About the Role
- You will own foundational infrastructure — the frameworks you build are the building blocks that every data pipeline and product feature at Credit Karma depends on
- You will work at real scale — hundreds of terabytes per day, millions of consumer profiles hydrated in real time, and strict SLAs that demand engineering rigor
- You will shape developer experience — designing the APIs, SDKs, and tooling that hundreds of engineers across the company interact with daily
- You will solve hard, novel problems — from building MySQL CDC pipelines with cloud-native encryption to designing Apache Beam framework SDKs that support both Java and Python
- You will be part of a high-impact, collaborative team with a strong culture of technical ownership and continuous learning
Minimum Basic Requirements
- 7+ years of professional software engineering experience building backend services and data infrastructure in Scala, Java, or a similar JVM language
- 7+ years of experience designing and operating high-throughput, low-latency distributed systems that process data at petabyte scale
- 3+ years of experience with streaming and messaging platforms such as Apache Kafka, Google Pub/Sub, or equivalent
- 3+ years of experience building data pipelines on a major cloud platform (GCP, AWS, or Azure), including services like Dataflow, BigQuery, Spanner, or their equivalents
- Professional experience with RPC frameworks such as Finagle, gRPC, or Akka for building production-grade service-to-service communication
- Strong understanding of software engineering best practices including CI/CD, version control (Git), code review, and automated testing
Qualifications
Preferred Qualifications
- Experience building reusable frameworks, SDKs, or platform libraries consumed by other engineering teams — you think about developer experience as a product
- Experience with Apache Beam (Dataflow) including custom transforms, side inputs, windowing strategies, and pipeline optimization
- Experience with Change Data Capture (CDC) patterns, particularly MySQL binlog-based replication to analytical stores
- Experience with data encryption at rest and in transit, including key management (KMS/GSM), SPIFFE/mTLS, and certificate authority integration
- Experience with schema management, data governance, and data quality frameworks in a large-scale production environment
- Familiarity with infrastructure-as-code, Kubernetes (GKE), and container-based deployment models
- Track record of mentoring engineers and driving technical alignment across teams through design documents and architecture reviews
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
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Get Access To All JobsTips for Finding Data Science Manager Jobs at Intuit
Frame your ML leadership with product impact
Intuit's Data Science Manager roles emphasize driving measurable outcomes across products like TurboTax, QuickBooks, and Credit Karma. Tailor your resume to show how you've led teams that shipped models into production, not just conducted research.
Verify Intuit's LCA filings before your interview
Search the DOL's OFLC disclosure database for Intuit's Labor Condition Applications under Data Science Manager titles. This confirms prevailing wage tiers and gives you a realistic anchor for compensation expectations before any offer conversation.
Clarify your visa category early in the process
Intuit sponsors multiple visa types including H-1B, E-3, TN, and F-1 OPT. Tell your recruiter your current status upfront so the hiring team can route your file to the right immigration counsel before an offer is extended.
Time your application around H-1B cap registration
If you need a cap-subject H-1B, USCIS registration opens in March for an October 1 start date. Align your Intuit interview timeline so an offer can be confirmed before the registration window closes, avoiding a full year's delay.
Highlight cross-functional leadership for the role
Intuit's hiring for Data Science Managers consistently prioritizes candidates who partner with product and engineering, not those who operate within a pure analytics silo. Prepare examples of influencing roadmap decisions with data insights across business units.
Use Migrate Mate to surface open Intuit roles
Intuit posts Data Science Manager openings across multiple locations and teams at different times of year. Use Migrate Mate to filter specifically for Intuit roles that match your visa type, so you apply to openings actively seeking sponsored candidates.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for Data Science Managers?
Yes, Intuit sponsors H-1B visas for Data Science Manager roles. Intuit is a large, established technology employer with a dedicated immigration program and outside counsel to manage filings. If you need H-1B sponsorship, confirm your timeline with the recruiter early, since cap-subject petitions must be filed well in advance of your intended start date.
How do I apply for Data Science Manager jobs at Intuit?
Apply directly through Intuit's careers portal or browse open roles filtered by visa type on Migrate Mate. Intuit's Data Science Manager roles typically require a completed application, a recruiter screen, a technical and leadership assessment, and several rounds of structured interviews covering analytical thinking, people management, and cross-functional collaboration. Tailoring your application to the specific product area strengthens your candidacy.
Which visa types does Intuit commonly use for Data Science Manager roles?
Intuit sponsors several visa categories for Data Science Manager positions, including H-1B, E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals, F-1 OPT and CPT for students nearing graduation, and J-1 visa for eligible exchange visitors. For permanent residency, Intuit also supports EB-2 and EB-3 Green Card pathways, which are common for senior individual contributors and managers who have been with the company.
What qualifications does Intuit expect for a Data Science Manager?
Intuit typically expects a graduate degree in a quantitative field such as statistics, computer science, or applied mathematics, combined with several years of experience managing data science teams. Strong candidates demonstrate hands-on expertise with machine learning workflows and can show they have translated model outputs into product or business decisions. Experience within fintech or consumer technology is a meaningful differentiator in the hiring process.
How do I plan my timeline if I need visa sponsorship for an Intuit Data Science Manager role?
If you need a cap-subject H-1B, plan for USCIS registration in March and an October 1 start date at the earliest. For E-3 or TN visas, processing is faster and not lottery-dependent, which gives you more flexibility on start dates. Intuit's immigration team works with outside counsel, so once an offer is extended, initiate the sponsorship conversation immediately to avoid delays caused by LCA certification timelines at the DOL.