Manager Data Analytics Engineer Jobs in Maine (NOW HIRING)

Our Finance Data Modernization team is seeking a Manager, Data Engineering. The Manager, Data Engineering leads a team responsible for designing and delivering scalable data pipelines, warehouse solutions, and governed data assets that support Finance analytics, operational reporting, and strategic business decision-making. This role partners closely with business and technology stakeholders to translate requirements into practical data solutions, drive consistency across a large portfolio of initiatives, and ensure smooth coordination from intake through implementation and operational support. The position provides technical leadership, advances modern data engineering practices, and champions the adoption of AI and agentic development processes to accelerate delivery while maintaining high standards for quality, governance, and business value. As a newly created leadership role, this position is critical to building consistency, scalability, and operational excellence across the Data Engineering function.

We are looking for Candidates in Chattanooga, TN or Portland, ME.

Principal Duties and Responsibilities

• Lead execution of the team's data strategy, providing direction on tools, methodologies, delivery practices, and engineering standards that support consistent and scalable outcomes.
• Oversee the planning, estimation, prioritization, and on-time delivery of data engineering initiatives, including setting clear expectations with business and technical stakeholders.
• Guide the design, development, and implementation of data pipelines, analytical databases, and analytics workflows that support operational reporting, Finance analytics, and business performance objectives.
• Partner with business areas to translate needs into technical plans, identify required data sources, communicate findings, and develop practical implementation approaches aligned to corporate policies, procedures, controls, and compliance requirements.
• Advance the team's use of AI and agentic development practices to accelerate developer throughput, improve delivery efficiency, and establish appropriate standards for prompt engineering, responsible usage, and team upskilling.
• Evaluate current and emerging data engineering, analytics, and AI methods to recommend continuous improvement opportunities and strengthen the team's technical capabilities.
• Recruit, train, coach, develop, and retain staff, including performance management and mentoring to build technical depth, delivery discipline, and effective use of modern data tools.
• Perform other related duties as assigned.

Job Specifications

Required Qualifications

• Minimum of 5 years of hands-on experience in data engineering, business intelligence, data science, or a closely related discipline, with demonstrated ability to deliver scalable data and analytics solutions.
  

Preferred Qualifications

• Bachelor's degree in Information Technology, Mathematics, Statistics, Computer Science, Data Analytics, or a related field preferred.
• Prior leadership, people management, or technical team leadership experience preferred.
  

Technical Skills

• Experience with Data Build Tool (DBT Core or Platform) to support data transformation, modeling, testing, documentation, and governed pipeline development.
• Experience with analytics programming languages, including SQL/Python, for data extraction, transformation, analysis, automation, and pipeline development.
• Experience with modern BI toolsets, including Tableau, Alteryx, PowerBI, or equivalent platforms, to support analytics, visualization, workflow automation, and business reporting needs.
• Strong understanding of data profiling, statistical analysis, data modeling, data architecture, and related infrastructure concepts across on-premises and cloud-based environments.
• Demonstrated ability to extract, load, integrate, and leverage data across data warehouses, transactional databases, object stores, APIs, and other enterprise data environments.
• Strong problem-solving, programming, prioritization, and project management skills, with the ability to manage ambiguity and make thoughtful recommendations.
• Ability to interpret complex technical and analytical information, decompose problems, and translate findings into practical business solutions for stakeholders at multiple levels.
• Excellent communication, collaboration, coaching, and mentoring skills, including the ability to develop technical talent and work effectively with business partners, technical teams, senior leaders, and external contacts.

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