AWS Data Engineer

VDart Inc; United States; On-site; USD 90,000 - 150,000; Full time

Job summary

VDart Inc. seeks an AWS Data Engineer for a remote, 6-month engagement to support critical data pipelines feeding the ECRM system. You will lead enhancements and apply deep data engineering knowledge across tools, processes, and environments.

The role requires strong AWS, Python, SQL, ETL, and Salesforce/ECRM data model expertise, plus experience with CI/CD, IaC, and secure data handling across multi-region architectures.

Qualifications

• Advanced SQL, SOQL, DB2, and Amazon Athena querying.
• Strong Python development, testing, and dependency management.
• Experience designing ETL and near-real-time data integration solutions.
• Hands-on experience with AWS Lambda, S3, SQS, SNS, EventBridge, Step Functions, AppFlow, Glue, Athena, and CloudWatch.
• Strong knowledge of Salesforce and ECRM data models, APIs, and bulk-data processing.
• Experience with IBM MQ, Kafka, and AWS messaging services for message-driven systems.
• Strong experience with REST APIs, OAuth, JWT, client secrets, certificates, and authentication troubleshooting.
• Experience with Terraform and OpenTofu for IaC.
• Proficient in Git, branching, merge requests, and code-review practices.
• Experience developing and managing GitLab CI/CD pipelines and deployment processes.
• Strong background in data validation, reconciliation, duplicate detection, and production resynchronization.
• Experience with monitoring, logging, alerting, and root-cause analysis.
• Hands-on experience with production support, incident response, and controlled recovery.
• Understanding of security, vulnerability remediation, encryption, and compliance requirements.
• Knowledge of active/standby, multi-region, failover, and disaster-recovery concepts.
• High-level understanding of global client architecture and enterprise systems.
• Strong experience in requirements analysis and translating business rules into technical logic.
• Skilled in creating technical documentation, architecture diagrams, runbooks, and automated change records.
• Strong cross-team consulting and communication with product owners, developers, infrastructure teams, and business stakeholders.
• Experience with risk assessment, change-impact analysis, and release coordination.
• Strong prioritization, independent problem-solving, and management of concurrent technical efforts.
• Experience using AI-assisted data engineering tools such as Codex and GitHub Copilot for development, research, troubleshooting, testing, automation, and technical reviews.
• Strong AI prompting, context management, output validation, and secure enterprise-data handling practices.

Responsibilities

• Lead and implement enhancements to critical data pipelines feeding the ECRM application.
• Collaborate with teams to optimize data engineering processes, tools, and environments.
• Apply data validation, reconciliation, and production-resynchronization to ensure reliability.

Skills

SQL

Python

ETL

AWS

Salesforce

CI/CD

IaC

Git/GitLab

Data validation

Monitoring/Logging

Security/compliance

Kafka/IBM MQ

REST APIs

Multi-region failover

Documentation

AI-assisted tooling

Tools

Terraform

OpenTofu

Git

GitLab CI/CD

Job description

Role Type: AWS Data Engineer

Location: Remote

Duration: 6 Months

Work Description:

• The resource will support critical data pipelines that feed data into our customer relationship management application (ECRM).
• The resources will be required to pick up and support these pipelines and work with the team on any enhancements that are needed.
• They should be able to apply in-depth knowledge of data engineering tools, processes, applications, programming languages, and environments to lead strategic work and utilize data and application architecture to increase efficiency and effectiveness of complex issues.

Business Knowledge:

Knowledge of Insurance domain, policy types, and data flows. Prior SF experience will be very beneficial.

Technical Skills:

• Advanced SQL, SOQL, DB2, and Amazon Athena querying.
• Strong Python development, testing, and dependency management.
• Experience designing ETL and near-real-time data integration solutions.
• Hands-on experience with AWS Lambda, S3, SQS, SNS, EventBridge, Step Functions, AppFlow, Glue, Athena, and CloudWatch.
• Strong knowledge of Salesforce and ECRM data models, APIs, and bulk-data processing.
• Experience with IBM MQ, Kafka, and AWS messaging services for message-driven systems.
• Strong experience with REST APIs, OAuth, JWT, client secrets, certificates, and authentication troubleshooting.
• Experience with Terraform and OpenTofu for Infrastructure as Code (IaC).
• Proficient in Git, branching, merge requests, and code-review practices.
• Experience developing and managing GitLab CI/CD pipelines and deployment processes.
• Strong background in data validation, reconciliation, duplicate detection, and production resynchronization.
• Experience with monitoring, logging, alerting, and root-cause analysis.
• Hands-on experience with production support, incident response, and controlled recovery.
• Understanding of security, vulnerability remediation, encryption, and compliance requirements.
• Knowledge of active/standby, multi-region, failover, and disaster-recovery concepts.
• High-level understanding of global client architecture and enterprise systems.
• Strong experience in requirements analysis and translating business rules into technical logic.
• Skilled in creating technical documentation, architecture diagrams, runbooks, and automated change records.
• Strong cross-team consulting and communication with product owners, developers, infrastructure teams, and business stakeholders.
• Experience with risk assessment, change-impact analysis, and release coordination.
• Strong prioritization, independent problem-solving, and management of concurrent technical efforts.
• Experience using AI-assisted data engineering tools such as Codex and GitHub Copilot for development, research, troubleshooting, testing, automation, and technical reviews.
• Strong AI prompting, context management, output validation, and secure enterprise-data handling practices.

Key Skills: Data Engineer, AWS, SQL, Python, ETL, Salesforce, Insurance