Data Engineering Lead

Eliassen Group; Charlotte (NC); Hybrid; USD 166,000 - 187,000; Full time

Benefits offered by this job

Medical, Dental, and Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a senior data engineering leader in Charlotte, NC on a hybrid model (3 days on-site). The role drives hands-on development and sets technical direction across enterprise data pipelines, governance, and AI-enabled analytics.

You will mentor engineers, influence architecture, and partner with stakeholders to deliver scalable, trustworthy data platforms. The position emphasizes reliability, observability, and performance across AWS environments, with a focus on scalable

Qualifications

• Leadership of hands-on development across multiple initiatives.
• Deep AWS experience, multi-account governance and security.
• Experience architecting data pipelines, ETL and orchestration.
• Ability to remediate data gaps and automate analytics.
• Proven high-reliability pipelines with observability.
• Background in data warehousing and performance optimization.
• Ability to influence architecture and communicate with stakeholders.
• Mentor data engineering teams and drive cross-functional work.

Responsibilities

• Lead hands-on development and provide technical direction.
• Set environments, standards, security controls and migration strategies.
• Architect and govern enterprise data pipelines and workflows.
• Identify gaps and implement scalable automation for analytics.
• Design reliable pipelines with data quality and observability.
• Build large-scale data warehousing balancing UX and performance.
• Drive architectural decisions and communicate with stakeholders.
• Mentor engineers and foster high-performing data culture.
• Lead cross-functional initiatives with data engineering, analytics, architecture, platform engineering, and business stakeholders.

Skills

Leadership

Hands-on development

AWS

Data governance

ETL pipelines

Observability

Python

SQL

Spark

MLOps

AI Bedrock

Data architectures

Tools

Databricks

Airflow

Kinesis

Azure

Kafka

Job description

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.

• Medical, Dental, and Vision benefits
• 401k with company matching
• life insurance

Rate: $80.00 to $90.00/hr. w2

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.