Data Engineer

Job Title: Data Engineer
Location: Boston, MA
Work Mode: Hybrid – 2 days per week onsite
Duration: 9 months (possible extension)
Interview Process: Recruitment Prescreening + 2 Technical Rounds + Client Interview

Job Summary

We are seeking an experienced Cloud Data Engineer / AWS Engineer to design, develop, and optimize scalable cloud-native data solutions for Liberty Mutual Investments.

The ideal candidate will bring 14+ years of overall IT experience, with strong expertise in Snowflake, SQL, data engineering, database design, and AWS infrastructure. This role involves developing high-performance data pipelines, optimizing cloud data platforms, and implementing scalable AWS solutions using Amazon S3, ECR, Fargate, Glue, Lambda, EC2, and Athena.

Candidates with investment domain experience, particularly Private Credit, are highly preferred. We will consider candidates with strong Data Engineering + AWS, Data Engineering + Private Credit, or AWS + Private Credit experience.

Key Responsibilities

• Design, develop, and maintain scalable cloud-native data architectures and solutions.
• Build, optimize, and support data pipelines using Snowflake, SQL, and AWS services.
• Design data models, database schemas, and data warehousing solutions for large-scale processing.
• Set up, configure, and manage AWS infrastructure, including Amazon S3, ECR, Fargate, Glue, Lambda, EC2, and Athena.
• Develop and maintain efficient ETL/ELT workflows and data integration processes.
• Implement automation, orchestration, and CI/CD pipelines using DevOps tools.
• Ensure data quality, performance, security, reliability, and operational efficiency.
• Collaborate with investment business teams, architects, and engineering stakeholders.
• Support API integrations, cloud automation, and data platform modernization initiatives.

Required Qualifications

• 14+ years of overall IT experience.
• 7+ years of Data Engineering experience, including scalable data pipelines and cloud-native architectures, for data engineering-focused profiles.
• Expert-level proficiency in SQL, including complex queries, performance tuning, data transformations, and large-scale processing.
• Strong hands-on experience with Snowflake, including cloud data warehousing, data processing, and optimization, for data engineering-focused profiles.
• Deep understanding of database design, data modeling, data architecture, and data warehousing.
• Strong AWS expertise, particularly Amazon S3, ECR, and Fargate, for AWS-focused profiles.
• Experience with related AWS services, including Glue, Lambda, EC2, and Athena.
• Experience implementing ETL/ELT pipelines, data ingestion, and workflow orchestration.
• Understanding of DevOps, CI/CD pipelines, GitHub Actions, Bamboo, and infrastructure automation.
• Strong problem-solving, communication, and stakeholder management skills.

Acceptable Skill Combinations

Candidates meeting any ONE of the following combinations will be considered:

Option 1: Data Engineering + AWS

• Strong Snowflake, SQL, and large-scale data processing experience.
• Expertise in database design, data modeling, and data warehousing.
• Hands-on AWS infrastructure experience with S3, ECR, Fargate, and related services.
• Python, Terraform, AWS CDK, and API integration experience are advantageous.

Option 2: Data Engineering + Private Credit

• Strong Data Engineering background with Snowflake, SQL, and ETL/ELT pipelines.
• Experience with database architecture, data modeling, and analytics platforms.
• Investment industry experience, specifically within Private Credit.

Option 3: AWS Engineering + Private Credit

• Strong AWS cloud infrastructure design, setup, and engineering experience.
• Hands-on experience with S3, ECR, Fargate, and related AWS infrastructure.
• Investment domain experience, particularly Private Credit.
• Understanding of financial data integrations and cloud-based data platforms.

Preferred Qualifications

• Private Credit or broader investment management domain experience.
• AWS CDK, Terraform, or Infrastructure as Code (IaC).
• Python scripting and REST API integration.
• CI/CD automation using GitHub Actions or Bamboo.
• Experience supporting cloud data platforms in financial services.
• Strong ownership mindset with the ability to work independently.

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent professional experience.