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Data Engineer Jobs in Maine (NOW HIRING)

Teamwass

Partner with Performance & Insights consultants, social analytics experts, paid media leads, digital account managers, and data/engineering partners to move ideas from ambiguity to useful output.

Unum UK

Data Scientist II - CX Analytics

Portland, ME · On-site +1

Programming & Process automation: Experience with file I/O, database integrations, and APIs to ... Data Visualization: Expertise on at least one visualization tool with working knowledge of others ...

NorthEastern

Data Scientist

Portland, ME

$87K - $123K/yr

D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field. * 0-2 years of industry, research, or applied project experience in data science or ...

Northeastern University

Data Scientist

Portland, ME · On-site

$87K - $123K/yr

D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field. * 0-2 years of industry, research, or applied project experience in data science or ...

Northeastern University

Data Scientist

Portland, ME · On-site

Responsibilities : • Perform data cleaning, exploratory data analysis (EDA), and feature engineering. • Train, evaluate, and compare machine learning models under supervision. • Assist with ...

Verdantas LLC

Data Analyst

Yarmouth, ME · On-site

$60 - $80/hr

At Verdantas, we're redefining environmental consulting and sustainable engineering through our use ... Verdantas is seeking a Data Analyst I who is eager to support stormwater invoicing and apply data ...

Verdantas

Data Analyst

Yarmouth, ME · On-site

$60 - $74/hr

At Verdantas, we're redefining environmental consulting and sustainable engineering through our use ... Verdantas is seeking a Data Analyst I who is eager to support stormwater invoicing and apply data ...

Verdantas

Data Analyst

Yarmouth, ME · On-site

$67K/yr

At Verdantas, we're redefining environmental consulting and sustainable engineering through our use ... We partner with clients to deliver smart, data-driven solutions to complex environmental and ...

Verdantas

Data Analyst

Yarmouth, ME

$67K/yr

At Verdantas, we're redefining environmental consulting and sustainable engineering through our use ... We partner with clients to deliver smart, data-driven solutions to complex environmental and ...

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Showing results 21-40

All JobsData Engineer JobsData Engineer Jobs in Maine

Data Engineer information

See Maine salary details

$43.1K

$125.6K

$171.9K

How much do data engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data engineer in Maine is $125,591.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,900.00 and $133,100.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Maine?

The most popular types of Data Engineer jobs in Maine are:

What are popular job titles related to Data Engineer jobs in Maine?

For Data Engineer jobs in Maine, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Maine look for?

The top searched job categories for Data Engineer jobs in Maine are:

What cities in Maine are hiring for Data Engineer jobs?

Cities in Maine with the most Data Engineer job openings:

What are popular job titles related to Data Engineer jobs in ME?

For Data Engineer jobs in ME, the most frequently searched job titles are:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Maine as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 79% Full Time, 15% Part Time, and 4% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $125,591 per year, or $60.4 per hour.

AI Data & Database Engineer - Modernization & AI Infrastructure

Portland, ME • On-site

WEX, Inc.
Software Development • 1 - 5K employees
Learn more about WEX, Inc.external

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

Key responsibilities

  • Analyze complex SQL Server stored procedures to identify embedded business logic, dependencies, and data access patterns.

  • Design and execute database migrations, refactoring stored procedures, and optimizing queries for high-volume workloads.

  • Build and maintain AI-native data infrastructure, including embedding pipelines, vector databases, and retrieval APIs.

WEX Inc. rating

7.3

Company rating: 7.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

13th of 21 rated payment service providers

Job description

WEX is looking for a Senior AI Data & Database Engineer to help modernize critical SQL Server systems while building the data infrastructure that powers AI applications and agents. This is a hands-on engineering role spanning database modernization, performance engineering, data pipelines, and AI-native retrieval infrastructure.
You'll work across two highly connected areas: modernizing complex legacy database systems by extracting business logic, improving performance, and enabling event-driven architectures; and building AI-ready data capabilities including embedding pipelines, vector search, RAG infrastructure, and retrieval services.
We're looking for someone who enjoys solving hard data problems and is excited to use AI as an engineering accelerator. You'll use tools such as GitHub Copilot, Cursor, and Claude Code to analyze legacy code, generate and validate migration scripts, troubleshoot performance issues, and automate database engineering workflows.
What You'll Do
Database Modernization & Performance
  • Analyze complex SQL Server stored procedures and identify embedded business logic, dependencies, and data access patterns.
  • Refactor stored procedures using established architectural patterns to simplify data access, improve maintainability, and enable business logic to move into services.
  • Design and execute database migrations while maintaining data integrity, availability, and backward compatibility.
  • Analyze execution plans, optimize queries, and design effective indexing strategies for high-volume workloads.
  • Implement event-driven database patterns including CDC, outbox patterns, and event publishing.
  • Build automated tests and validation processes for database changes, migrations, and refactored procedures.
  • Create structured, AI-consumable documentation including annotated schemas, procedures, dependencies, and system context.
AI-Native Data Infrastructure
  • Build embedding pipelines covering text extraction, preprocessing, chunking, embedding generation, and vector storage.
  • Implement and optimize vector databases, vector indexes, semantic search, and hybrid retrieval patterns.
  • Build synchronization pipelines that keep vector stores aligned with source systems.
  • Develop retrieval APIs and services consumed by AI applications and agents.
  • Implement evaluation and monitoring for RAG systems, including retrieval quality, latency, relevance, and data freshness.
  • Partner with AI/ML engineers to improve embedding strategies, retrieval quality, and overall AI data performance.
Data Platform Engineering
  • Design and implement reliable ETL/ELT pipelines across SQL Server, PostgreSQL, Snowflake, and cloud data services.
  • Build API-based ingestion, event streaming, and batch-processing workflows.
  • Implement data quality, validation, observability, and operational monitoring for data pipelines.
  • Develop infrastructure-as-code for database provisioning and configuration using Terraform and ARM/Bicep.
  • Support NoSQL data solutions including MongoDB and Cosmos DB, with a focus on data modeling and query performance.
  • Design data access patterns that support domain-driven architectures, including repositories, query services, and read models.
AI-Assisted Engineering
  • Use AI coding assistants daily to accelerate database analysis, code generation, debugging, testing, and documentation.
  • Develop prompts, scripts, and workflows that apply AI to database engineering and modernization challenges.
  • Contribute to AI-powered engineering tools such as stored procedure analyzers, schema documentation generators, and migration assistants.
  • Create structured context and artifacts that enable AI agents and coding tools to reason effectively about data systems.
  • Evaluate emerging AI tools and identify practical opportunities to improve engineering productivity.
Collaboration & Engineering Excellence
  • Partner with application, platform, and AI/ML engineers to design scalable, reliable data solutions.
  • Participate in code and architecture reviews for database, data platform, and AI infrastructure changes.
  • Troubleshoot complex production data and performance issues and contribute to operational support as needed.
  • Document technical decisions, patterns, and solutions so knowledge is reusable across engineering teams.
  • Mentor engineers on database design, performance optimization, data engineering, and modern engineering practices.
What You'll Bring
  • Strong hands-on experience with SQL Server, T-SQL, stored procedures, query optimization, and execution plans.
  • Proven experience modernizing legacy database systems and decomposing complex database logic into maintainable application or service architectures.
  • Strong understanding of relational database design, indexing, transactions, data integrity, and performance engineering.
  • Experience building production-grade data pipelines and integrating data through APIs, events, and batch processes.
  • Experience with one or more modern data platforms such as PostgreSQL, Snowflake, MongoDB, or Cosmos DB.
  • Practical experience with vector databases, embeddings, semantic search, RAG, or AI data pipelines.
  • Understanding of event-driven architectures and patterns such as CDC and transactional outbox.
  • Experience with cloud platforms and infrastructure-as-code, preferably AWS/Azure and Terraform.
  • Strong software engineering fundamentals, including version control, automated testing, CI/CD, and code review practices.
  • Demonstrated ability to use AI coding assistants effectively and willingness to incorporate AI into day-to-day engineering work.
Preferred Qualifications
  • Experience building data infrastructure specifically for LLM or agentic applications.
  • Experience with vector databases such as Pinecone, Azure AI Search, OpenSearch, pgvector, or similar technologies.
  • Experience with Kafka or other event-streaming platforms.
  • Experience developing retrieval services or RAG evaluation frameworks.
  • Experience creating internal AI-powered developer tools or automation.
  • Experience working in large-scale, distributed, cloud-native environments.
How You'll Make an Impact
You'll play a key role in transforming how WEX manages and uses data-from modernizing foundational SQL Server systems to building the retrieval and data infrastructure required for the next generation of AI applications. This role is ideal for an engineer who enjoys deep technical problem-solving and wants to work at the intersection of database engineering, modernization, and AI infrastructure.
The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.

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