Lead Enterprise Data Engineer
About The Position
Coastal Waste & Recycling is seeking a Lead Enterprise Data Engineer to lead the design, development, and reliability of its enterprise data platform. This hands-on technical leadership role focuses on building scalable, reliable, and well-governed data solutions for reporting, analytics, operational decision-making, integrations, and future AI initiatives. The role partners with technology and business teams to strengthen the company’s data foundation, improve pipeline performance and reliability, and modernize how data moves across the organization. The position provides technical direction and mentoring while contributing directly to data engineering work and production support. It collaborates with Enterprise Data Operations, Enterprise Analytics, Operations, Finance, Sales, People Experience, and IT to translate business and technical requirements into scalable solutions, and supports organizational growth initiatives such as acquisitions, system integrations, and entry into new markets.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field, or equivalent professional experience.
- 7+ years of experience in data engineering, data integration, ETL/ELT development, data warehousing, or cloud data platform engineering.
- 2+ years of experience serving as a technical lead, senior engineer, solution architect, platform owner, or similar role on enterprise data projects.
- Strong experience with Snowflake administration and SQL development.
- Strong experience with Azure Data Factory or comparable enterprise data integration tools.
- Experience with cloud data architecture, API and third-party integrations, Git-based source control, and CI/CD practices.
- Experience supporting production data platforms with established monitoring, data quality, access controls, and change management practices.
- Strong troubleshooting, documentation, communication, and collaboration skills.
- Ability to explain technical concepts clearly to both technical and business stakeholders.
Nice To Haves
- Master’s degree in Computer Science, Information Systems, Data Engineering, Business Administration, or a related field.
- Microsoft Azure or Snowflake SnowPro certification.
- Experience with Python, Azure DevOps, dbt or similar transformation frameworks, Microsoft Fabric, Databricks, MDM, data governance, lakehouse architectures, or AI/ML data pipelines.
- Experience supporting a multi-location or operationally complex organization.
- Experience supporting high-growth organizations, acquisitions, or system integrations.
- Bilingual English/Spanish preferred.
Responsibilities
- Serve as a technical leader for enterprise data engineering initiatives.
- Design, develop, and optimize data pipelines, ingestion frameworks, transformations, and orchestration workflows.
- Administer and optimize Snowflake environments, including databases, schemas, warehouses, roles, grants, performance, and cost management.
- Develop and maintain Azure Data Factory pipelines, triggers, integration runtimes, and data movement processes.
- Establish monitoring, alerting, retry, and failure-recovery processes for critical data pipelines.
- Build and maintain data quality controls, including source-to-target validation, reconciliation, exception handling, and supporting documentation.
- Support integrations with enterprise applications, third-party systems, APIs, cloud services, and approved data-sharing solutions.
- Follow established change management, release, and CI/CD processes for production pipelines, database objects, integrations, and platform changes.
- Partner with Enterprise Data Operations, Enterprise Analytics, Operations, Finance, Sales, People Experience, and IT to translate business and technical requirements into scalable data solutions.
- Identify opportunities to improve data engineering processes through automation, reusable frameworks, standardization, and improved monitoring.
- Support the reliability and performance of production data platforms and troubleshoot technical issues as needed.
- Maintain technical documentation for data pipelines, integrations, architecture, and production support processes.
- Support data needs related to acquisitions, system integrations, new markets, and other business growth initiatives.
- Provide technical direction, mentoring, and quality review for data engineers, analysts, contractors, and implementation partners.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
