[Remote] Snowflake Lead Data Engineering
Note: The job is a remote job and is open to candidates in USA. Diverse Lynx is seeking a Snowflake Lead Data Engineering professional to support and advance cloud-based data platforms for insurance applications. The role leads Snowflake architecture, production support, data ingestion and transformation, security, and AI/ML enablement, including analytics use cases such as claims triage, fraud detection, and pricing analytics.
Responsibilities
- Snowflake Production Support
- Perform root cause analysis for job failures and data analysis & fixes
- Perform Month End Closing Activities
- Snowflake Development & Architecture
- Lead design and development of Snowflake schemas, tables, views, streams, tasks, and Snowpipes
- Define and enforce best practices for performance optimization (warehouse sizing, clustering, query tuning)
- Own Snowflake security architecture: RBAC, role hierarchy, data masking, row/column level security
- Oversee promotion of code across environments using CI/CD practices
- Data Engineering & Integration
- Lead development of batch and near real time ingestion pipelines using Talend / Qlik Replicate / Snowpipe
- Ensure data quality checks, reconciliation, and schema drift handling
- Guide integration from insurance source systems (Policy, Claims, Billing, Reinsurance) into Snowflake
- Provide technical oversight for SQL, Python, and ELT based transformations
- AI / Advanced Analytics Enablement
- Enable AI/ML use cases on Snowflake, including:
- Feature engineering datasets for ML models
- Snowpark (Python)–based data processing
- Integration with external ML platforms (Databricks / SageMaker / Azure ML where applicable)
- Support AI driven insights such as:
- Claims triage & risk scoring
- Fraud detection inputs
- Premium leakage and pricing analytics
- Guide teams in using Python, SQL, and Snowflake native capabilities for data science workloads
Skills
- Snowflake, Cortex AI, Python and Insurance Domain on AWS Cloud, Talend ETL
- • Snowflake: Advanced SQL, Performance Tuning, Security, Snowpipe, Streams & Tasks
- • Data Engineering: ELT/ETL patterns, data modeling, CDC concepts
- • Hands on exposure to AI/ML pipelines (feature preparation, training data creation)
- • Experience supporting ML models through data engineering and operationalization
- • Familiarity with Python ML libraries (scikit learn, pandas, NumPy) – applied from a data engineering perspective
- • Understanding of model lifecycle support (data refresh, monitoring, retraining inputs)
- • Strong communication skills for onsite customer interaction
- • Ability to translate business requirements into scalable data & AI solutions
- • Python: Data processing, automation, Snowpark (preferred)
- • Strong understanding of cloud data platform architecture (AWS preferred)
- • Insurance domain experience (P&C / Specialty Insurance strongly preferred)
Benefits
- Remote work arrangement
Company Overview
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