Data Engineer
About the job
- A bachelor's degree or at least three years of relevant work experience.
- A bachelor's degree in Engineering with Honors in Data Science or Computer Science, along with at least one year of hands-on experience building large-scale data processing platforms.
- Strong understanding of data warehousing concepts, including entity-relationship data modeling, data warehouse architecture, feature engineering, and the five Vs of the Big Data ecosystem.
- At least one year of practical experience using SQL, Hive, and PySpark for data extraction, aggregation, optimization, and storage on Hadoop technologies (Spark, Tez, MapReduce) and cloud platforms.
- At least one year of applied generative AI engineering experience, including production-grade generative AI features such as retrieval-augmented generation over enterprise data, prompt engineering, evaluation, guardrails, and familiarity with large language models, vectorization, chunking, and orchestration frameworks such as LangChain.
- Ability to build reusable components, including prompt libraries, evaluation frameworks, vector store abstractions, and integration software development kits and application programming interfaces for reuse across Finance scenarios.
- At least one year of hands-on experience delivering end-to-end business intelligence solutions, understanding extract, transform, load strategies, and ability to contribute to data model decisions for reporting.
- Collaborate with Data Analysts, Data Scientists, Software Engineers, and cross-functional partners to design, build, and deploy scalable data pipelines that deliver high-quality, governed analytical datasets across Finance domains.
- Engineer high-quality batch and streaming data pipelines using SQL, Hive, and PySpark across Lake/Lakehouse environments to power curated finance domain marts and a governed semantic layer.
- Design dimensional and semantic models that enable self-service analytics using Power BI, Fabric semantic models, and SSAS Tabular, with performant DAX measures and row-level security.
- Ship production-grade generative AI features, including retrieval-augmented generation and prompt-chaining or agents, on governed datasets; implement vectorization strategies and chunking that respect personally identifiable information and Sarbanes-Oxley controls.
- Partner with data science and machine learning teams to train, fine-tune, and evaluate models; harden prompt templates, guardrails, and content filters; and track hallucination, toxicity, and retrieval metrics such as precision, recall, and hit@k.
- Build reusable components, including prompt libraries, evaluation harnesses, vector store abstractions, and integration software development kits and application programming interfaces for reuse across Finance use cases.
- Implement continuous integration and continuous delivery for data and AI using Git, Azure DevOps, or GitHub Actions; implement data quality tests using Great Expectations or an equivalent; and automate model and data deployment using MLflow, Fabric, or Azure Machine Learning.
- Define observability for lineage, drift, freshness, and cost, with alerts and service-level agreements; drive continuous hardening for performance, including SQL and DAX tuning, cost efficiency, and reliability.
- Deliver high-impact dashboards and scorecards using Power BI or Tableau, along with governed certified datasets; coach analysts on best-practice modeling and performance tuning.
- Embed privacy by design, including personally identifiable information masking and purpose limitation, finance controls including Sarbanes-Oxley and audit trails, and robust documentation such as runbooks, data dictionaries, and model cards.
- Working knowledge of machine learning, deep learning, generative AI, and MLOps.
- Familiarity with data administration, including YARN, Splunk, Profiler, Perfmon, security architecture, user provisioning, and audit.
- Exposure to Finance Data Analytics or the finance domain.
About the company
Visa runs a global payment network that connects banks, merchants and consumers so card purchases and money transfers move between financial institutions. Its VisaNet system handles authorization, clearing and settlement, linking the bank behind a buyer's card with the bank that accepts a merchant's payment. The company earns fees from payment activity, transaction processing and international transactions, and sells fraud prevention tools, payment software and consulting services to businesses. Banks and other partners issue Visa branded cards and use its technology to build their own payment products. Visa traces its roots to a Bank of America card program launched in 1958 and is headquartered in San Francisco.
Company Size
10,001+
Company Stage
N/A
Total Funding
$9.6M
Headquarters
San Francisco, California
Founded
1958
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Simplify's Take
What believers are saying
- Visa demand keeps growing: July 2026 results showed quarterly revenue up 14% to $11.6 billion.
- Advisory staff get structured training: Visa University has over 50 learning modules for its consulting and analytics teams.
- Visa is capturing stablecoin activity: September 2026 settlement volume exceeded a $20 billion annualized run rate.
What critics are saying
- Visa must pay partners more: July 2026 results showed client incentives up 18%, faster than revenue.
- Visa faces pressure on its debit contracts: the Justice Department seeks restrictions on alleged anticompetitive practices.
- Technology and product jobs face cuts: Visa announced about 2,600 planned layoffs in July 2026.
What makes Visa unique
- Visa reaches everyday checkout at scale: its cards are accepted at over 175 million merchant locations.
- Visa avoids consumer lending exposure: it bears no cardholder credit risk.
- Visa Direct extends beyond cards: it reaches approximately 12 billion bank account, wallet and card endpoints.
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Benefits
Health Insurance.
Life Insurance.
Dental Insurance.
Disability Insurance.
Accidental Death & Dismemberment Insurance.
Company News
Kenyan fintech HoneyCoin raised $4.9 million in seed funding to expand its stablecoin cross-border payment services into Africa, Latin America, and Asia. Led by Flourish Ventures, the round included TLcom Capital, Stellar Development Foundation, and Visa Ventures. HoneyCoin processes $150 million monthly, serving 350 enterprise clients. The funds will be used to hire executives, secure licenses, and expand into new markets, with plans for new products by Q3 2025.
Nekuda raises $5M led by Madrona, Amex Ventures & Visa Ventures to power agentic aayments. For the infrastructure of the future of online commerce.
Visa Ventures has invested in stablecoin infrastructure platform BVNK, marking Visa's first direct investment in a stablecoin payments player. This move supports the future of stablecoins in payments, enhancing BVNK's credibility and penetration with Visa's partners. BVNK, which raised $50 million in a Series B round in December 2024, processes $12 billion in annualized volume and offers solutions for B2B and B2C payments using stablecoins.