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Dbt Analytics Jobs in Portland, ME (NOW HIRING)

Spark Tek Inc

QA Data Engineer

Freeport, ME · On-site

$118K - $142K/yr

Responsibilities : • Partner with Data Engineers, Analysts, and business stakeholders to define ... Great Expectations, dbt tests). • Familiarity with LL Bean data and business process. • ...

Unum UK

Manager, Data Engineering

Portland, ME · On-site

Experience with Data Build Tool (DBT Core or Platform) to support data transformation, modeling, testing, documentation, and governed pipeline development. * Experience with analytics programming ...

TEKsystems

Data Engineer

Westbrook, ME · On-site +1

$62/hr

Designs and implements scalable, reliable distributed data processing frameworks and analytical ... dbt Cloud Proficiency with Spark SQL, Python Streaming ingestion patterns including schema ...

TEKsystems

Data Engineer

Westbrook, ME · On-site +1

$62/hr

Designs and implements scalable, reliable distributed data processing frameworks and analytical ... dbt Cloud Proficiency with Spark SQL, Python Streaming ingestion patterns including schema ...

All JobsDbt Analytics JobsDbt Analytics Jobs in Portland, ME

Dbt Analytics information

See Portland, ME salary details

$38.4K

$65.4K

$94.1K

How much do dbt analytics jobs pay per year?

As of Sep 7, 2026, the average yearly pay for dbt analytics in Portland, ME is $65,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,200.00 and $72,600.00 per year, depending on experience, location, and employer.

What is a dbt analytics?

A dbt Analytics job typically refers to a role focused on using dbt (data build tool) to transform, test, and document data within a data warehouse. Professionals in this field design and manage data models, write SQL-based transformations, and ensure data quality for analytics purposes. They collaborate with data engineers and analysts to build efficient, maintainable workflows that support business intelligence and data-driven decision-making. dbt Analytics jobs require strong SQL skills, familiarity with modern data stack tools, and an understanding of data modeling best practices.

What are the key skills and qualifications needed to thrive as a dbt analytics professional?

To thrive as a DBT Analytics professional, you need strong SQL skills, a solid understanding of data modeling, and experience with analytics engineering, typically backed by a degree in a quantitative field. Familiarity with the DBT (Data Build Tool) platform, cloud data warehouses like Snowflake or BigQuery, and version control systems such as Git is essential. Attention to detail, problem-solving abilities, and effective communication help you collaborate with stakeholders and ensure data reliability. These skills and tools are crucial for transforming raw data into actionable insights and maintaining robust, scalable analytics infrastructure.

How does a dbt analytics professional typically collaborate with data engineers and analysts within a team?

Dbt Analytics professionals play a key role in bridging the work of data engineers and data analysts. They transform raw data into clean, well-documented, and analysis-ready datasets using dbt (data build tool), ensuring consistency and reliability. Collaboration often involves working closely with data engineers to understand data sources and pipelines, while also partnering with analysts to tailor data models to business needs. Effective communication and regular feedback loops are crucial, as dbt professionals often serve as the link between technical data infrastructure and business-facing analysis.

What is the difference between Dbt Analytics vs Data Analyst?

AspectDbt AnalyticsData Analyst
Required CredentialsSQL, data modeling, analytics certificationsStatistics, Excel, SQL, sometimes certifications
Work EnvironmentData teams, analytics platforms, cloud environmentsBusiness units, reporting tools, spreadsheets
Industry UsageData transformation, modeling, analytics pipelinesData interpretation, reporting, insights

While Dbt Analytics focuses on transforming and modeling data within analytics workflows, Data Analysts primarily interpret data and generate reports. Both roles require SQL skills and work closely with data teams, but Dbt Analytics emphasizes data transformation using tools like dbt, whereas Data Analysts focus on analyzing and communicating insights.

Is dbt in demand?

Dbt analytics engineers are increasingly in demand as organizations adopt modern data transformation tools to improve data workflows. Skills in SQL, data modeling, and familiarity with cloud platforms enhance job prospects in this field, which is growing alongside the broader data analytics industry.

What are popular job titles related to Dbt Analytics jobs in Portland, ME?

For Dbt Analytics jobs in Portland, ME, the most frequently searched job titles are:

What job categories do people searching Dbt Analytics jobs in Portland, ME look for?

The top searched job categories for Dbt Analytics jobs in Portland, ME are:

Dbt Analytics jobs near you
Infographic showing various Dbt Analytics job openings in Portland, ME as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $65,381 per year, or $31.4 per hour.

Software Development Engineer 2- Data Engineering

WEX, Inc.

Portland, ME • On-site

$117K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

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

About the Role
Are you a technical artisan who thrives in collaborative environments and gets excited about solving the right problems, the right way? Do you believe in breaking down silos and fostering a culture of shared responsibility? Then this role is for you! In today's software development and data landscape, collaboration, end-to-end (E2E) accountability, problem-solving, and streamlined workflows are key to achieving efficiency and delivering high-quality solutions that solve customer problems and generate business outcomes.
We believe in the power of integrated engineering, where development, data quality, architecture, and agility skills blend together throughout the solution delivery pipeline.
As a Software Development Engineer 2 (SDE 2) focusing on Data Engineering & Data Architecture, you will be a champion for this approach. You will own the data pipelines and modeling that power our Customer Data Platform (CDP), directly feeding marketing/commercial segmentation and customer journeys. In this role, you will match the expectations of an Intermediate Individual Contributor (EAE 2), acting with independence to own specific modules, functional areas, and data models without constant oversight.
How you'll make an impact
  • Domain: Data Engineering & Data Architecture for a Customer Data Platform (CDP) feeding marketing/commercial segmentation and journeys.
  • Primary Tech Stack: Snowflake, dbt (Data Build Tool), CI/CD Automation.
  • Preferred Tech Stack: Salesforce Core, Salesforce Data360 (DataCloud).

Experience you'll bring
1. Data Modeling & Pipeline Engineering
  • Design and build robust data models in Snowflake using dbt, spanning from staging through to production data marts, ensuring they are resilient, cost-effective, and maintainable.
  • Integrate, stage, and reconcile data from multiple complex source systems (e.g., Siebel CRM, Enterprise Data Warehouse (EDW) snapshots, portfolio health hubs) into a unified Customer Data Platform.
  • Add field enhancements and manage the evolution of the CDP Mart to power downstream segmentation and outbound journeys.
2. Architecture & Technical Governance
  • Own feature-level architecture decisions and author Architecture Decision Records (ADRs)-evaluating alternative technical approaches and documenting recommended paths for technical sign-off.
  • Manage the dbt "lakefront" project structure, establishing model ownership, group permissions, and approved-team configurations to safely enable team self-service and decentralized model changes.
  • Contribute to the evolution of team "Golden Paths", service communication standards, and data orchestration workflows.
3. Data Discovery & Complex Business Logic Execution
  • Translate complex commercial and marketing rules
  • Perform deep-dive data discovery, technical feasibility assessments, and data volume analysis to quantify business impact and ensure scalability before committing to a build.
4. Stakeholder Alignment & Team Collaboration
  • Partner actively across engineering, analytics, product, and business stakeholders to reconcile conflicting business logic, align definitions, and drive consensus toward a single source of truth.
  • Lead feature-level demonstrations and facilitate technical alignment workshops with product managers and cross-functional teams to resolve ambiguity.
  • Mentor Level 1 engineers through pair programming, structured knowledge-sharing sessions, and constructive, empathetic code/configuration reviews.
5. Quality Assurance & AI-Augmented Workflows
  • Take ownership of feature-level data quality, designing automated regression tests and verification checks to balance risk versus test coverage.
  • Implement, debug, and leverage AI-augmented engineering workflows (e.g., GitHub Copilot, basic LLM integrations, or automated prompt configurations) to optimize pipeline efficiency and code readability while verifying all outputs against strict enterprise standards.

Qualifications & Requirements
  • Experience: 3-5 years of professional experience in data engineering, data warehousing, or a software development engineering role focusing on data.
  • Snowflake Proficiency: Proven track record of independently designing and building highly scalable data models and staging environments inside Snowflake.
  • dbt (Data Build Tool): Strong hands-on experience managing dbt projects, testing, documentation, and source-control-driven data pipelines.
  • Preferred Experience: Direct hands-on experience or familiarity with Salesforce Data360 / DataCloud (CDP) ingestion, mapping, and orchestration patterns.
  • CI/CD & DevOps: Proficient experience utilizing CI/CD automation tools, managing branches, and executing automated code/data quality gates.
  • Problem-Solving: Strong analytical capability to break down abstract business constraints into concrete data exclusions, filtering matrixes, and performance-tuned queries.

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.
Pay Range: $96,100.00 - $115,500.00

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