AWS Data Engineer

ValueMomentum; Pennsylvania; On-site; USD 160,000 - 230,000; Full time

Job summary

ValueMomentum seeks a highly experienced AWS Data Engineer to lead design, modernization, and implementation of scalable, cloud-native data platforms. You will drive enterprise data transformation, partnering with stakeholders, data teams, and leadership to define data strategies, architectures, and execution roadmaps.

The role demands hands-on delivery, architectural leadership, and the ability to deliver end-to-end data solutions across Data Lake/Warehouse/Lakehouse on AWS, Snowflake, and

Qualifications

• 14+ years of experience in data architecture and data engineering roles.
• Proven experience as an AWS Data Solution Architect.
• Hands-on expertise with AWS data services.
• Strong understanding of data Modeling, ETL/ELT, and analytics platforms.
• Experience modernizing large-scale, complex data environments.
• Excellent communication and stakeholder management skills.

Responsibilities

• Lead the end-to-end architecture and design of enterprise data platforms on AWS.
• Define and drive data modernization strategies, including migration from legacy platforms to cloud-native architectures.
• Provide hands-on architectural guidance and contribute to solution delivery alongside data engineering teams.
• Establish data architecture standards, patterns, and best practices across the organization.
• Design scalable Data Lake, Data Warehouse, and Lakehouse architectures leveraging AWS, Snowflake, and Apache Iceberg.
• Develop technology roadmaps aligned with business and data strategy.
• Act as a trusted advisor to business and technology leadership.
• Collaborate with security, infrastructure, and DevOps teams to ensure compliant and secure data solutions.

Skills

Data architecture

Data engineering

Architectural leadership

Communication

Stakeholder management

Cloud data platforms

ETL/ELT design

Big data ecosystems

Tools

AWS data services

Snowflake

Apache Iceberg

Amazon S3

Redshift

Glue

Athena

EMR

Lambda

Step Functions

RDS

DynamoDB

DB2

Mainframe

DataStage

WebFocus

SAS

Qlik

Job description

We are seeking a highly experienced AWS Data Engineer to lead the design, modernization, and implementation of scalable, cloud-native data platforms. The ideal candidate brings strong architectural leadership, hands-on delivery experience, and a future-focused mindset to drive enterprise data transformation initiatives. This role requires close collaboration with business stakeholders, data engineering teams, and leadership to define data strategies, modern architectures, and execution roadmaps.

Required Qualifications

• 14+ years of experience in data architecture and data engineering roles.
• Proven experience as an AWS Data Solution Architect.
• Deep hands-on expertise with AWS data services.
• Strong understanding of data Modeling, ETL/ELT, and analytics platforms.
• Experience modernizing large-scale, complex data environments.
• Excellent communication and stakeholder management skills.

Key Responsibilities

• Lead the end-to-end architecture and design of enterprise data platforms on AWS.
• Define and drive data modernization strategies, including migration from legacy platforms to cloud-native architectures.
• Provide hands-on architectural guidance and contribute to solution delivery alongside data engineering teams.
• Establish data architecture standards, patterns, and best practices across the organization.
• Design scalable Data Lake, Data Warehouse, and Lakehouse architectures leveraging AWS, Snowflake, and Apache Iceberg.
• Develop technology roadmaps aligned with business and data strategy.
• Act as a trusted advisor to business and technology leadership.
• Collaborate with security, infrastructure, and DevOps teams to ensure compliant and secure data solutions.

AWS & Data Platform Expertise

• Architect solutions using AWS data services, along with Snowflake and Apache Iceberg, including:
• Amazon S3, Redshift, Glue, Athena, EMR.
• AWS Lambda, Step Functions.
• Amazon RDS, DynamoDB.
• Design and optimize batch and real-time data pipelines.
• Implement data ingestion, transformation, and orchestration frameworks across AWS, Snowflake, and Iceberg-based Lakehouse platforms.
• Ensure high availability, performance optimization, and cost efficiency.

Legacy & Modernization Experience

• Strong understanding of legacy data ecosystems, including:
• DB2, Mainframe, DataStage.
• NoSQL platforms.
• WebFocus, SAS, Qlik.
• Lead migration initiatives from on-prem / legacy systems to AWS cloud-native platforms, including Snowflake and Iceberg-based Lakehouse architectures.
• Modernize reporting, analytics, and data processing workloads.
• Introduce AI-driven initiatives to improve data engineering productivity and operational efficiency.
• Leverage automation for data quality, monitoring, and governance.
• Evaluate emerging technologies and market solutions to continuously evolve the data platform.

About ValueMomentum:

ValueMomentum is a leading solutions provider for the global property and casualty insurance industry, supported by deep domain and technology capabilities. We help insurers stay ahead with sustained growth and high performance for enhancing stakeholder value and fostering resilient societies. Trusted by over 100 insurers, ValueMomentum is one of the largest services providers exclusively focused on property and casualty. ValueMomentum is headquartered in Piscataway, NJ, with state-of-the-art delivery centers in Piscataway, NJ; Hyderabad, Pune, and Coimbatore in India; Toronto in Canada; and London in the United Kingdom.

ValueMomentum is an Equal Opportunity Employer committed to fostering a diverse and inclusive workplace.

We make all employment decisions based on qualifications, merit, and business needs, without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, protected veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law.

We are also committed to providing reasonable accommodation for qualified individuals with disabilities and applicants throughout the recruitment process, in accordance with applicable laws.