Lead Data Engineer

Harnham; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Harnham is seeking a Lead Data Engineer to drive the evolution of a cloud-based data platform supporting analytics and business decisions. The role focuses on modernizing data infrastructure, building scalable data ecosystems, and enabling reliable, high-performance data operations.

The ideal candidate brings deep cloud data engineering expertise, platform automation, and strong leadership to deliver trusted data solutions and governance across the organization.

Qualifications

• 5+ years of experience in Data Engineering or related field.
• Proven experience building enterprise-scale data platforms.
• Strong cloud-native data architectures and modern data engineering practices.
• Experience designing scalable pipelines and automation frameworks.

Responsibilities

• Design, develop, and maintain scalable data pipelines for analytics and reporting.
• Build automated data ingestion frameworks for diverse data sources.
• Develop semantic data models for trusted reporting cross-organization.
• Design and implement ELT/ETL solutions using cloud-native technologies.
• Automate workflow orchestration, monitoring, and operations for reliability.
• Partner with stakeholders and architects to deliver scalable data solutions.
• Optimize cloud data platform performance, queries, and cost management.
• Implement testing, observability, deployment automation, and data quality practices.
• Contribute to data governance and metadata management.
• Provide technical leadership and mentor engineers.

Skills

Cloud data engineering

Python

SQL

ETL/ELT

CI/CD

Data governance

Stakeholder mgmt

Mentoring

Tools

Airflow

dbt

Terraform

Job description

A leading organization is seeking a Lead Data Engineer to play a key role in the continued evolution of its cloud-based data platform. This is an opportunity to join a growing team focused on modernizing enterprise data infrastructure, enabling advanced analytics, and building scalable solutions that support data-driven business decisions.

The successful candidate will bring strong expertise in cloud data engineering, platform automation, and modern data architecture, along with a passion for building reliable, high-performance data ecosystems.

Responsibilities

• Design, develop, and maintain scalable data pipelines supporting enterprise analytics and reporting initiatives.
• Build and enhance automated data ingestion frameworks for a variety of structured and semi-structured data sources.
• Develop semantic data models that deliver trusted, consistent reporting across the organization.
• Design and implement robust ELT/ETL solutions using modern cloud-native technologies.
• Automate workflow orchestration, monitoring, and operational processes to improve platform reliability.
• Partner with business stakeholders, analytics teams, and architects to deliver scalable data solutions.
• Optimize cloud data platform performance, query efficiency, and cost management.
• Implement best practices for testing, observability, deployment automation, and operational support.
• Contribute to data governance, metadata management, and data quality initiatives.
• Provide technical leadership, mentor engineers, and help drive engineering excellence across the team.

Required Experience

• 5+ years of experience in Data Engineering, Data Platform Development, or a related field.
• Proven experience building and maintaining enterprise-scale data platforms.
• Strong background in cloud-native data architectures and modern data engineering practices.
• Expertise designing and implementing scalable data pipelines and automation frameworks.
• Strong understanding of dimensional modeling, semantic layers, and data architecture principles.
• Advanced SQL development skills.
• Strong Python programming experience.
• Hands-on experience building and optimizing ELT/ETL processes.
• Experience with CI/CD pipelines, infrastructure automation, and DevOps best practices.
• Experience implementing data quality, monitoring, and observability solutions.Excellent communication and stakeholder management skills.

Desired Technical Background

• Cloud data warehouse technologies
• Cloud object storage platforms
• Workflow orchestration tools
• Large-scale data processing and ingestion frameworks
• Data modeling and semantic layer development
• Infrastructure as Code and deployment automation
• Enterprise analytics and reporting ecosystems