Data Platform Engineer II

🔥 0 minutes ago

🇲🇽 Mexico – Remote

💵 $612k - $857k / year

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Spring Financial

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

💸 Finance

💳 Fintech

👥 B2C

Finance • Fintech • B2C

Spring Financial is a financial services company in Canada offering a range of loan products including personal loans, mortgages, and credit-building solutions. They provide same-day personal loans up to $35,000 and offer products like the Evergreen Loan for responsible borrowing and The Foundation for credit building. Spring Financial operates primarily online, allowing customers to apply for loans in minutes without visiting a branch. With interest rates starting at 9. 99%, they ensure a hassle-free borrowing experience with flexible repayment options. Over 250,000 Canadians have received financing from Spring Financial, making it a trusted choice for financial needs.

📋 Description

• Build and maintain scalable, secure, and reliable data pipelines and platform components across AWS and Snowflake • Help scope and deliver initiatives that modernize legacy data flows, bring together batch and streaming sources, and enable self-serve analytics • Apply and help improve engineering standards around testing, observability, security, and CI/CD within data systems • Build AI capabilities into data pipelines, including anomaly detection and automated tagging • Use AI in development practices, including assisted testing and documentation • Stay current on agentic and AI-driven data platform workflows and share learnings with the team • Work with engineers and business partners to clarify requirements, surface risks, and propose practical solutions • Partner with Analytics, ML, Finance, and other business teams to deliver data meeting latency, accuracy, and governance needs • Communicate technical work, constraints, and trade-offs to non-technical partners • Contribute to technical design discussions, code reviews, and the evolution of data architecture • Own problems through production while maintaining quality, documentation, and engineering standards • Develop technical judgment through peer collaboration and share knowledge with the team

🎯 Requirements

• Solid experience building data pipelines using Snowflake and AWS-native tools (e.g., Glue, Lambda, Redshift, Step Functions) • Working experience with real-time data systems such as Kafka, Kinesis, Flink, or Spark Streaming • Good working knowledge of data modeling, schema evolution, and secure, privacy-conscious data design • Fluency in Python and SQL • Some exposure to infrastructure-as-code (e.g., Terraform or CDK) • Practical use of AI tools in your development workflow, and interest in building AI into the platform itself • Track record of delivering projects end to end, with an eye on the business value behind them • Strong communication and collaboration skills; a reliable partner to both engineering and business teams • Self-directed in ambiguity: comfortable asking good questions, acting on feedback, and taking on broader scope over time • Experience with dbt or analytics engineering patterns (nice to have) • Familiarity with ML platform tooling or feature store design (nice to have) • Background in fintech, credit risk, or other regulated data environments (nice to have)

🏖️ Benefits

• The flexibility to work fully remotely from anywhere in Mexico • A collaborative environment that supports learning, innovation, and professional growth • The opportunity to work on business-critical data infrastructure and platform initiatives with meaningful ownership and impact • Hands-on exposure to AWS, Snowflake, real-time data systems, and modern data engineering practices, with opportunities to explore and build AI-enabled capabilities