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Data Engineer (Only EST 14+ Yrs preferred)

KONNECTINGTREE INCBoston, MA🇺🇸United StatesPosted Oct 20, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Boston, MA, United States
Posted
Yesterday
SQLGitAWSETLSnowflakeBambooGitHub ActionsCI/CD

Job Description

Position: Data Engineer
Location: Boston, MA (Hybrid)
Type: Contract
Role Summary
We are seeking a Cloud Data Engineer to design and deliver scalable, cloud-native data solutions for Liberty Mutual Investments. The role requires deep expertise in database design, Snowflake, SQL, and data processing, complemented by strong hands-on experience with AWS infrastructure setup, including Amazon S3, Amazon ECR, AWS Fargate, and related services.
Key Responsibilities
  • Design and maintain scalable data and cloud solutions.
  • Build and optimize data pipelines and AWS infrastructure.
  • Collaborate with business and technology stakeholders.
  • Ensure data quality, security, and operational excellence.
  • Support cloud-native integrations and automation initiatives.
Ideal Candidate Profile
  • 14+ years of overall IT experience.
  • 7+ years of experience in data engineering, with a proven track record of designing, building, and optimizing scalable, cloud-native data pipelines and architectures.
  • Experience in the investment domain, specifically Private Credit, is required.
  • Expert-level proficiency in SQL, with strong experience in large-scale data processing, transformation, automation, and orchestration.
  • Deep expertise in database design, data modeling, data warehousing, and data architecture best practices.
  • Strong hands-on expertise in Snowflake for building and optimizing cloud-based data warehousing and processing solutions.
  • Strong hands-on experience setting up AWS infrastructure, including Amazon S3, Amazon ECR, and AWS Fargate, with advanced proficiency in related services such as AWS Glue, AWS Lambda, Amazon EC2, and Amazon Athena.
  • Proficiency in designing and implementing ETL/ELT pipelines and data-loading patterns for data warehouses and data lakes.
  • Solid experience with DevOps practices and automation frameworks, including CI/CD pipelines, GitHub Actions, Bamboo, and pipeline-as-code principles.

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