AIFT
Virtual Insurance
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at AIFT. Skills: data engineering, data platform architecture, AI/ML engineering, modern cloud data platforms, BI data foundations, GenAI / LLM architectures, SQL, workflow orchestration tools, streaming platforms, pipeline design, data warehouse development, dimensional modeling, data governance, data lineage, data privacy, data security. own day-to-day operations of data platforms/pipelines capacity, stability, upgrades, deployments, and recovery drills. design/manage mult”
Industry & Context.
problem-solving skills; debugging; performance tuning
What They're Looking For.
Must Have
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, Proficiency in SQL, workflow orchestration tools (e.g., Airflow), streaming platforms (e.g., Kafka), pipeline design best practices, Solid understanding of data warehouse development lifecycles, dimensional modeling concepts, debugging skills, performance tuning skills, problem-solving skills, Working knowledge of data governance, lineage, privacy, security frameworks
Nice to Have
modern cloud data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift), Hands-on experience building BI data foundations, supporting GenAI / LLM architectures, Familiarity with GitLab, CI/CD pipelines
What You'll Do.
own day-to-day operations of data platforms/pipelines capacity
design/manage multi-source ingestion
Develop rule-based and statistical data quality checks
Implement automated remediation
reconciliation workflows
and historical backfilling
Establish monitoring and alerting frameworks
plan and maintain scalable ETL/ELT including scheduling
Enforce data access controls
Apply Infrastructure-as-Code
Contribute to embedded GenAI and LLM-powered data applications
Partner with analytics and product teams to operationalize AI-driven data solutions
How You'll Work.
Team & Collaboration
Partner with analytics and product teams
Full Job Description
[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 d
Applying for this Senior Data Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Greenhouse
- Create a Greenhouse profile before applying — it saves time across multiple applications.
- Upload your resume as a PDF; the parser handles it better than Word.
- Answer all knockout questions carefully — wrong answers auto-reject before a human sees you.
- Enable email notifications to track application status in real time.
ANONYMOUS · UNFILTERED
What do employees actually say about AIFT?
Real rants from real employees. Read before you apply.