Data Engineering Lead

Eliassen Group; Charlotte (NC); Hybrid; USD 110,000 - 124,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k with company matching

Life insurance

Job summary

Eliassen Group in Charlotte, NC seeks a senior data engineering leader to drive hands-on development while setting technical direction across initiatives. Responsibilities include architecting and governing enterprise-scale data pipelines, ETL processes, and ingestion workflows in AWS, with emphasis on reliability, data quality, observability, and performance.

You will mentor engineers, influence architecture, and partner with cross-functional stakeholders to advance analytics, governance, and

Qualifications

• Proven leadership of hands-on development with oversight across multiple initiatives.
• Deep experience with AWS environments, infrastructure standards, security controls, and multi-account strategies.
• Track record architecting and governing enterprise data pipelines, ETL, and orchestration.
• History of remediating data gaps and deploying scalable automation for analytics.
• Experience delivering high-reliability pipelines with strong data quality and observability.
• Background in large-scale data warehousing and performance optimization.
• Experience influencing architectural direction and communicating with diverse stakeholders.
• Mentorship and team-building for data engineering teams.

Responsibilities

• Lead hands-on development and provide technical direction, code reviews, and engineering oversight across multiple initiatives.
• Establish development environments, infrastructure standards, security controls, and migration strategies across multiple AWS accounts and environments.
• Architect, develop, and govern enterprise-scale data pipelines, ETL processes, ingestion frameworks, and orchestration workflows.
• Identify data gaps, define remediation plans, and implement scalable automation to improve analytical capabilities.
• Design and implement reliable data pipelines emphasizing data quality, observability, resiliency, and operational supportability.
• Build and optimize large-scale data warehousing solutions that balance user experience and system performance.
• Drive technical decision-making and communicate complex concepts to technical and non-technical stakeholders.
• Mentor engineers and foster a high-performing data engineering culture.
• Lead cross-functional initiatives with data engineering, analytics, architecture, platform engineering, and business stakeholders.

Skills

Leadership

AWS

Data governance

Observability

MLOps

Python

SQL

Stakeholder communication

Mentoring

Cloud architectures

Tools

Databricks

Spark

SQL

Python

Bedrock

LLMs

Vector databases

Job description

Hybrid 3 days on-site in Charlotte, NC

Our client seeks a senior data engineering leader who will drive hands-on development while setting technical direction across multiple initiatives. The role requires expertise in architecting, building, and governing enterprise-scale data pipelines and platforms across cloud environments, with a focus on reliability, quality, observability, and performance. The leader will mentor engineers, influence architectural decisions, and partner with cross-functional stakeholders to advance analytics, governance, and AI-enablement.

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: $80.00 to $90.00/hr. w2

JN -102026-109016

Responsibilities

• Lead hands-on development and provide technical direction, code reviews, and engineering oversight across multiple initiatives.
• Establish development environments, infrastructure standards, security controls, and migration strategies across multiple AWS accounts and environments.
• Architect, develop, and govern enterprise-scale data pipelines, ETL processes, ingestion frameworks, and orchestration workflows.
• Identify data gaps, define remediation plans, and implement scalable automation to improve analytical capabilities.
• Design and implement reliable data pipelines emphasizing data quality, observability, resiliency, and operational supportability.
• Build and optimize large-scale data warehousing solutions that balance user experience and system performance.
• Drive technical decision-making and communicate complex concepts to technical and non-technical stakeholders.
• Mentor engineers and foster a high-performing data engineering culture.
• Lead cross-functional initiatives with data engineering, analytics, architecture, platform engineering, and business stakeholders.

Experience Requirements

• Proven leadership of hands-on development with oversight across multiple initiatives.
• Deep experience with AWS environments, infrastructure standards, security controls, and multi-account strategies.
• Track record architecting and governing enterprise data pipelines, ETL, and orchestration.
• History of remediating data gaps and deploying scalable automation for analytics.
• Experience delivering high-reliability pipelines with strong data quality and observability.
• Background in large-scale data warehousing and performance optimization.
• Experience influencing architectural direction and communicating with diverse stakeholders.
• Mentorship and team-building for data engineering teams.
• Cross-functional leadership across engineering and business functions.
• Preferred: AWS cloud certifications, data governance and metadata platforms, real-time and event-driven architectures, streaming platforms, data mesh and lakehouse patterns, cloud transformation programs, AI application development with AWS Bedrock or similar, AI-ready pipelines and MLOps, proficiency in Python, SQL, Spark, Generative AI, hands-on with AWS, Azure, Databricks, knowledge of LLMs, RAG, vector databases, AI search, and responsible AI, governance, data quality, security, and compliance.

Education Requirements