AI Summary
Design, build, and optimize scalable data pipelines and platforms for analytics, AI/ML, and business intelligence use cases. Collaborate with cross-functional teams to support data-driven decision making. Strong experience in data engineering and cloud environments required.
Key Highlights
Design and operate FinOps data platforms
Develop secure data models and APIs
Analyze cloud usage and financial datasets
Key Responsibilities
Support the design and operation of FinOps data platforms
Design, build, and maintain scalable data pipelines
Develop secure data models and APIs
Technical Skills Required
Benefits & Perks
Visa sponsorship available
Hybrid work model
Full-time employment
Nice to Have
Experience operating data platforms supporting financial, billing, or cost attribution use cases
Familiarity with FinOps concepts
Job Description
- leading Automotive Tech companies
- highly skilled and motivated Data Engineer
- A robust data platform in AWS/Azure Cloud Environment
📍 Tokyo, Japan (Hybrid Work Model)
🕒Type: Full-Time
🌐Language: English,
🚗 Industry: Automotive Tech / Cloud & AI / FinOps
💼 Visa sponsorship available
We are looking for a Data Platform Engineer to design, build, and optimize scalable data pipelines and platforms that support analytics, AI/ML, and business intelligence use cases. You will work closely with Data Analyst, data scientists, software engineers, and product teams in a highly collaborative, international environment.
If you are interested to learn more, email to Betrand.Chris@teksystems.com
🔧 Key Responsibilities
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- Support the design and operation of FinOps data platforms enabling cost attribution, chargeback, showback, and cloud usage analytics.
- Design, build, and maintain scalable data pipelines for cloud usage, license consumption, and financial datasets across Stargate and Enterprise AI environments.
- Develop secure data models, APIs, and access layers to support dashboards, reporting, and downstream analytics.
- Ensure data quality, reliability, performance, and observability through automation, monitoring, and validation frameworks.
- Translate financial governance and business requirements into scalable technical implementations.
- Automate and standardize cloud cost and usage workflows to reduce manual processing and improve operational efficiency.
- Analyze cloud usage and financial datasets to generate structured insights for leadership and engineering teams.
- Strong experience in data engineering within cloud environments (AWS, Azure, or GCP).
- Proficiency in Python and SQL, with production-grade pipeline development experience.
- Hands-on experience with modern data warehouse/lakehouse architectures.
- Familiarity with API development (FastAPI or similar).
- Experience with orchestration and transformation tools such as Airflow, DBT, Snowflake, Databricks, or equivalent.
- Strong understanding of data quality, monitoring, and automation.
- Excellent problem‑solving skills and ability to collaborate with cross-functional teams.
Explore our comprehensive directory of visa sponsorship jobs from employers worldwide who are ready to sponsor talented international professionals.
- Experience operating data platforms supporting financial, billing, or cost attribution use cases.
- Familiarity with FinOps concepts (chargeback, showback, cloud cost optimization).
- Experience with infrastructure-as-code and platform automation (Terraform, CI/CD pipelines).
- Strong stakeholder management and communication skills in global teams.
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