# Senior Data Engineer, Virtual Insurance at AIFT

> Taiwan · Senior · Data engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Aaift%3A5810418004 (read 2026-11-09).

## Facts (observed)

- Company: [AIFT](https://alderhq.app/companies/aift)
- Location text: Taiwan; Taiwan Office
- Where it can be done from (inferred): Taiwan (evidence: "Location: Taiwan; Taiwan Office")
- Posted: 2026-02-24 (258 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/aift/jobs/5810418004
- Skills listed (inferred): Kafka, Airflow, Snowflake, SQL, LLMs

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

\[Job Overview\]

We are looking for an experienced Senior Data Engineer to join our engineering team and play a key role in building and scaling our enterprise data platform. You will design, develop, and maintain high-quality data warehouses and data-driven applications that power analytics, reconciliation, and business decision-making across the organization.

This role requires strong expertise in modern data architectures, pipeline engineering, and data quality management. The ideal candidate combines hands-on technical capability with a deep commitment to reliability, scalability, and governance in a regulated environment.

\[Responsibilities\]

· Data operations: own day-to-day operations of data platforms/pipelines capacity, stability, upgrades, deployments, and recovery drills to sustain high availability and low latency.

· Data collection: design/manage multi-source ingestion (exchanges, internal and external systems), protocol parsing, and robust retry mechanisms.

· Develop rule-based and statistical data quality checks (completeness, uniqueness, time alignment, anomaly detection, error handling).

· Implement automated remediation, reconciliation workflows, and historical backfilling.

· Establish monitoring and alerting frameworks to ensure trusted, production-grade datasets.

· End-to-End pipelines: plan and maintain scalable ETL/ELT including scheduling, caching, partitioning, modelling, schema evolution, and lineage to support both batch and real-time streaming.

· Enforce data access controls, encryption, auditing, and classification to comply with internal policies and external regulatory requirements (including PII management).

· Apply Infrastructure-as-Code, data versioning, data tests, and CI/CD to improve predictability and reduce manual risk.

· Contribute to embedded GenAI and LLM-powered data applications for enterprise analytics, reconciliation, and internal productivity use cases.

· Partner with analytics and product teams to operationalize AI-driven data solutions.

\[Requirements\]

· Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.

· 5+ years of experience in data engineering, data platform architecture, or AI/ML engineering.

· Strong experience with modern cloud data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift).

· Hands-on experience building BI data foundations and supporting GenAI / LLM architectures.

· Proficiency in SQL and workflow orchestration tools (e.g., Airflow), streaming platforms (e.g., Kafka), and pipeline design best practices.

· Solid understanding of data warehouse development lifecycles and dimensional modeling concepts.

· Familiarity with GitLab and CI/CD pipelines.

· Strong debugging, performance tuning, and problem-solving skills.

· Working knowledge of data governance, lineage, privacy, and security frameworks.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aaift%3A5810418004 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.