Lead Data Engineer

Eliassen Group; Charlotte (NC); Hybrid; Confidential; Full time

Benefits offered by this job

Medical, Dental, Vision

401k with company matching

Life insurance

Job summary

Eliassen Group, on behalf of its client in Charlotte, NC, seeks a Lead Data Engineer to own architecture and delivery of scalable data platforms on AWS. You will lead design of data lakes and warehouses, govern IAM and security, and implement resilient pipelines using PySpark, Python, and SQL.

The role requires mentoring engineers, driving standards for quality and observability, and partnering with architects and stakeholders to align solutions with enterprise objectives.

Qualifications

• 8+ years in data engineering with 5+ years on AWS.
• Expertise with S3, EMR, Glue, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions.
• Experience creating AI apps with AWS Bedrock.
• Strong background in data lakes and warehouses ( Lake Formation, Redshift, Athena ).
• Extensive Kafka streaming experience (Confluent).
• Advanced SQL and data modeling (dimensional, data vault).
• Hands-on PySpark on EMR and Python development.
• Terraform for infrastructure as code; CI/CD with GitHub Actions.
• Knowledge of AWS IAM, governance and security; data governance and observability.
• Experience with Generative AI concepts, LLMs, RAG, vector DBs, and MLOps.

Responsibilities

• Lead design, architecture, and implementation of enterprise data solutions across AWS.
• Partner with developers, data scientists, architects, product owners, and stakeholders to define strategy.
• Provide technical leadership and mentorship to data engineers and promote best practices.
• Drive architectural decisions for scalability, security, reliability, and maintainability.
• Oversee data lake and data warehouse solutions ( Lake Formation, Redshift, Athena ).
• Establish standards for data modeling, ETL, pipeline reliability, monitoring, and operations.
• Lead end-to-end delivery aligned to business requirements and regulatory needs.
• Oversee production support of AWS data platforms and optimize performance.
• Champion data quality, governance, observability, and stewardship.
• Identify modernization opportunities with automation and cloud-native tech.

Skills

AWS

PySpark

SQL

Kafka

Terraform

CI/CD

GitHub Actions

IAM & security

Data governance

MLOps

Tools

Lake Formation

Redshift

Athena

EMR

S3

Glue

Lambda

CloudWatch

Step Functions

Airflow

Job description

Description:

Hybrid 3 on in Charlotte, NC

Our client seeks a Lead Data Engineer to own architecture and delivery of scalable data platforms on AWS. The role will lead design of data lakes and warehouses, govern IAM and security, and implement resilient pipelines using Python, PySpark, and SQL. The leader will mentor engineers, drive standards for quality and observability, and partner with architects and stakeholders to align solutions with enterprise objectives. Experience with Kafka streaming, Terraform, CI/CD, and orchestration is required. Knowledge of Bedrock, LLMs, RAG, vector databases, and MLOps will support AI-ready pipelines and responsible AI practices.

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $85.00 to $95.00/hr. w2

Responsibilities:

• Lead design, architecture, and implementation of enterprise data solutions across AWS.
• Partner with developers, data scientists, architects, product owners, and stakeholders to define technical strategy and scalable solutions.
• Provide technical leadership and mentorship to data engineers and promote engineering best practices.
• Drive architectural decisions to ensure scalability, security, reliability, and maintainability.
• Design and oversee data lake and data warehouse solutions using Lake Formation, Redshift, and Athena.
• Establish standards for data modeling, ETL frameworks, pipeline reliability, monitoring, and operations.
• Lead end-to-end delivery aligned to business requirements, enterprise standards, and regulatory needs.
• Oversee production support of AWS data platforms, perform root-cause analysis, and optimize performance.
• Champion data quality, governance, observability, and stewardship across platforms and teams.
• Identify modernization opportunities using automation and cloud-native technologies.

Experience Requirements:

• 8+ years in data engineering with 5+ years on AWS.
• Expertise with S3, EMR, Glue, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions.
• Experience creating AI applications with AWS Bedrock.
• Strong background in data lakes and warehouses with Lake Formation, Redshift, and Athena.
• Extensive experience with Kafka streaming, preferably Confluent Kafka.
• Advanced SQL and data modeling including dimensional and data vault.
• Deep experience building scalable and resilient pipelines in AWS.
• Hands‑on PySpark on EMR and advanced Python development.
• Expertise with Terraform for Infrastructure as Code.
• CI/CD with GitHub and GitHub Actions.
• Deep knowledge of AWS IAM roles, policies, governance, and security best practices.
• Workflow orchestration with Step Functions, Airflow, or similar.
• Leadership in cloud migration, modernization, and enterprise data platforms.
• Strong understanding of data governance, metadata, data quality, and observability.
• Proficiency with Generative AI concepts, LLMs, RAG, vector databases, and MLOps.
• Experience with Azure or Databricks is a plus.