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Snowflake Lead Data Engineering

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Onsite

Snowflake Lead Data Engineering

Tata Consultancy Services

Snowflake Lead Data Engineering

Skills

SQL QueriesData EngineeringPythonData ScienceNumPypandasSnowflakeDatabricksData AnalysisMachine LearningAIAWSTalendAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

12 September 2026

What they need


Must Have Technical/Functional Skills

Snowflake, Cortex AI, Python and Insurance Domain on AWS Cloud, Talend ETL

Roles & Responsibilities

The Snowflake Lead will serve as the onsite technical lead for CLEARBROOK ’s enterprise data platform, responsible for end to end Snowflake solution design, development leadership, and AI/advanced analytics enablement. The role requires deep hands on expertise in Snowflake, strong data engineering fundamentals, and the ability to integrate AI/ML driven use cases into the Snowflake ecosystem while coordinating with offshore teams.

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

Core Technical Skills

  • Snowflake: Advanced SQL, Performance Tuning, Security, Snowpipe, Streams & Tasks
  • Data Engineering: ELT/ETL patterns, data modeling, CDC concepts
  • Python: Data processing, automation, Snowpark (preferred)
  • Strong understanding of cloud data platform architecture (AWS preferred)

AI / Analytics Skills

  • 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)

Domain & Soft Skills

  • Insurance domain experience (P&C / Specialty Insurance strongly preferred)
  • Strong communication skills for onsite customer interaction
  • Ability to translate business requirements into scalable data & AI solutions

Salary Range: $110,000 to $130,000 per year

Qualifications: BACHELOR OF COMPUTER SCIENCE

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