Data Engineer IV- #26-23312

US Tech Solutions; Charlotte (NC); On-site; USD 138,000 - 152,000; Full time

Job summary

US Tech Solutions seeks a senior data engineering leader to design and implement enterprise data solutions on the AWS stack. You will drive architecture decisions, mentor teams, and partner with stakeholders to deliver scalable, secure, and observable data platforms.

You will oversee data pipelines, governance, and modernization efforts, leveraging PySpark, Databricks, and AI-ready workflows to support business insights and analytics at scale.

Qualifications

• 8 years of experience in Data Engineering
• 5 years AWS workload experience
• S3/EMR/Glue expertise
• Lambda, Athena, CloudWatch, Step Functions experience
• Experience with AWS Bedrock AI apps
• Enterprise data lake/warehouse design (Lake Formation, Redshift, Athena)
• Kafka-based streaming architectures
• Advanced SQL and data modeling (dimensional, data vault)
• Data pipelines in AWS, PySpark
• Terraform IaC
• CI/CD with GitHub Actions
• AWS IAM, security governance
• Workflow orchestration (Airflow, Step Functions)
• Cloud migration and modernization leadership
• Data governance, metadata, quality, observability

Responsibilities

• Lead design and implementation of enterprise data engineering on AWS
• Collaborate with tech and business to define scalable strategies
• Provide technical leadership and mentorship to data engineers
• Drive architectural decisions with data and solution architects
• Design data warehouse/lake solutions balancing usability and performance
• Set engineering standards for data modeling, ETL, pipeline reliability, monitoring
• Oversee end-to-end delivery aligning with enterprise architecture
• Lead production support for AWS-based data platforms and optimize performance
• Champion data quality, governance, observability, and stewardship
• Identify modernization opportunities using automation and cloud-native tech
• Guide hands-on development while providing direction and reviews
• Establish dev environments, security controls, and migration strategies
• Architect and govern enterprise-scale data pipelines and ingestion
• Drive data quality, resiliency, and operational supportability
• Mentor engineers and grow high-performing teams
• Coordinate cross-functional initiatives with analytics and architecture
• Communicate complex concepts to diverse stakeholders
• Lead AI-ready data pipelines and ML workflows

Skills

AWS Data Engineering

S3/EMR/Glue

Lambda/Athena

Redshift

Kafka

PySpark

Terraform

GitHub Actions

Airflow

Data Modeling

Data Lake

Data Warehouse

IAM Security

Data Governance

AI with Bedrock

Python

SQL

ETL/ELT

Spark

Observability

Databricks

Tools

Databricks

Confluent Kafka

Terraform

GitHub

Job description

$100-$110 per hour

Charlotte, NC

Contract

Duration: 12 months

Core Technical Skills

8 years of experience in Data Engineering with at least 5 years working extensively within AWS ecosystems

Expert-level experience with AWS services including S3, EMR, Glue Jobs, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions

Experience creating AI applications with AWS Bedrock

Strong experience designing and implementing enterprise-scale data lake and data warehouse solutions using Lake Formation, AmClienton Redshift, and AmClienton Athena

Extensive experience with Kafka-based streaming architectures, preferably Confluent Kafka

Advanced SQL and data modeling expertise, including dimensional modeling, data vault, and large-scale data warehousing solutions

Deep experience designing, developing, and optimizing scalable, resilient data pipelines within AWS environments

Strong understanding of distributed data processing frameworks, particularly PySpark and EMR

Expert knowledge of database management principles, performance tuning, and data architecture best practices

Advanced Python development skills with extensive hands-on experience using PySpark

Expertise in Infrastructure as Code using Terraform

Experience designing and implementing CI/CD frameworks using GitHub and GitHub Actions

Deep knowledge of AWS IAM roles, policies, governance, and security best practices

Strong experience with workflow orchestration tools such as AWS Step Functions, Apache Airflow, or equivalent platforms

Experience leading cloud migration, modernization, and enterprise data platform initiatives

Strong understanding of data governance, metadata management, data quality frameworks, and observability principles

Core Responsibilities

Lead the design, architecture, and implementation of enterprise data engineering solutions across the AWS ecosystem

Collaborate with Lead Developers, Data Scientists, Architects, Product Owners, and business stakeholders to define technical strategy and scalable solutions

Provide technical leadership and mentorship to Data Engineers and development teams, promoting engineering excellence and best practices

Drive key architectural decisions in partnership with Data Architects and Solution Architects to ensure scalability, security, reliability, and maintainability

Design and oversee data warehouse and data lake solutions that balance business usability, performance, and long-term sustainability

Establish engineering standards for data modeling, ETL frameworks, pipeline reliability, monitoring, and operational excellence

Lead end-to-end solution delivery, ensuring alignment with business requirements, enterprise architecture standards, and regulatory requirements

Oversee production support and operational management of AWS-based data platforms, driving root‑cause analysis and performance optimization initiatives

Champion data quality, governance, observability, and data stewardship practices across platforms and teams

Identify opportunities to modernize data architecture and improve operational efficiency through automation and cloud-native technologies

Core Experience and Abilities

Ability to lead hands-on development efforts while providing technical direction, code reviews, and engineering oversight across multiple initiatives

Experience establishing development environments, infrastructure standards, security controls, and migration strategies across multiple AWS accounts and environments

Ability to architect, develop, and govern enterprise-scale data pipelines, ETL processes, data ingestion frameworks, and orchestration workflows

Proven ability to identify data gaps, define strategic remediation plans, and implement scalable automation solutions that improve analytical capabilities across the organization

Ability to design and implement highly reliable data pipelines with strong focus on data quality, observability, resiliency, and operational supportability

Experience building and optimizing large-scale data warehousing solutions that prioritize both business user experience and system performance

Ability to drive technical decision-making, influence architectural direction, and effectively communicate complex technical concepts to both technical and non-technical stakeholders

Proven track record mentoring engineers, fostering technical growth, and building high-performing data engineering teams

Experience leading cross-functional initiatives involving data engineering, analytics, architecture, platform engineering, and business stakeholders

Strong problem-solving and leadership skills with the ability to manage competing priorities in fast-paced enterprise environments

Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps.

Proficiency in Python, SQL, Spark, and Generative AI technologies for scalable data and analytics solutions.

Hands-on experience with AWS, Clienture, or Databricks and cloud-based AI/data platforms.

Knowledge of LLMs, RAG, and vector databases to support AI-powered applications and intelligent search.

Strong understanding of data governance, quality, security, and responsible AI practices.

Preferred Qualifications

AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud certifications

Experience implementing enterprise data governance and metadata management platforms

Experience with real-time analytics, event-driven architectures, and streaming data platforms

Knowledge of modern data architecture patterns including Data Mesh, Lakehouse, and domain-oriented design

Experience leading large-scale cloud transformation or enterprise data modernization programs

About US Tech Solutions:

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com .

US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

AI Statement:

By applying, you acknowledge that AI-assisted tools may be used during hiring.

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