Technology

Lead Data Engineer- Snowflake Cortex+ AWS Bedrock

Tekaccel, IncUnited States🇺🇸United StatesPosted Sep 23, 2026

Why This Role Stands Out

This hybrid role offers a unique opportunity to shape cutting-edge data and AI platforms, leveraging Snowflake Cortex and AWS Bedrock for advanced generative AI solutions. You'll thrive here if you're a proactive engineer passionate about building reliable, scalable systems and driving innovation in a supportive environment. Join a forward-thinking team and gain invaluable experience in a rapidly evolving field.

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

United States

Posted

4 weeks ago

ShellAPI GatewayAWSEncryptionSnowflakeGenerative AILLMPythonTerraform

Job Description

Senior/ Lead Data Engineer- Snowflake Cortex+ AWS Bedrock

Location : Remote

We are looking for an experienced Site Reliability Engineer (SRE) to support and operate highly available Snowflake and AWS-based data and AI platforms, with hands-on exposure to Snowflake Cortex and Amazon Bedrock.

The engineer will be responsible for platform reliability, monitoring, incident management, automation, performance optimization, security, and operational support for data and Generative AI workloads.

Key Responsibilities

Design, deploy, monitor, and maintain highly available AWS, Snowflake, and GenAI platforms.
Support Snowflake Cortex capabilities for AI/ML and Generative AI workloads.
Work with Amazon Bedrock to integrate and operate foundation models and GenAI applications.
Monitor infrastructure, applications, data pipelines, APIs, and AI workloads.
Define and monitor SLIs, SLOs, and SLAs for critical services.
Implement observability using CloudWatch, logs, metrics, traces, and alerting.
Troubleshoot production incidents and perform Root Cause Analysis (RCA).
Participate in on-call / production support and incident management.
Automate repetitive operational activities using Python, Shell scripting, Terraform, or AWS services.
Build and maintain CI/CD pipelines for application, data, and AI workloads.
Optimize Snowflake compute usage, query performance, warehouse utilization, and cost.
Monitor and troubleshoot Snowflake data pipelines and workloads.
Support AWS services such as S3, Lambda, IAM, CloudWatch, ECS/EKS, API Gateway, and Secrets Manager.
Implement security, access controls, encryption, secrets management, and least-privilege IAM.
Monitor the reliability and performance of LLM/GenAI applications using Amazon Bedrock.
Track AI application metrics such as latency, throughput, errors, token usage, and cost.
Establish automated health checks, alerts, recovery mechanisms, and disaster-recovery procedures.
Collaborate with Data Engineers, ML Engineers, Developers, Architects, Product Managers, and business stakeholders.
Continuously improve platform reliability through automation, observability, capacity planning, and performance engineering.