1

Evening Analytics Engineer Dbt Jobs (NOW HIRING)

Design, build, and maintain certified dbt models as the authoritative source for business-critical metrics. * Establish and enforce analytics engineering standards for modeling, testing ...

Our Analytics Engineering team sits within a hub-and-spoke model, partnering closely with Go-To ... Design dimensional data models (dbt) for core entities such as accounts, pipeline, performance, and ...

Analytics Engineer Product Boston, MA At Klaviyo, we value the unique backgrounds, experiences and ... Design dimensional data models (dbt) for core entities such as accounts, pipeline, performance, and ...

Design and build robust dbt models that serve as the authoritative foundation for analytics ... Partner with Engineering and Data Science to ensure our Snowflake data warehouse is well-structured ...

Design and build robust dbt models that serve as the authoritative foundation for analytics ... Partner with Engineering and Data Science to ensure our Snowflake data warehouse is well-structured ...

As an early member of the Analytics Engineering function, you will help define how data products ... You will design the dbt models and semantic layer that produce our certified business and financial ...

As an early member of the Analytics Engineering function, you will help define how data products ... You will design the dbt models and semantic layer that produce our certified business and financial ...

The role involves extensive work with SQL, DBT, and Python, as well as leveraging LLMs for data ... Required : • 6+ years of analytics engineering, data engineering, data science, or other highly ...

This role owns the dbt analytics transformation layer and dbt project stewardship, and partners with Data Engineering on upstream pipelines and data shaping to ensure analytics-ready inputs. This ...

We're looking for a builder - an Analytics Engineer who thinks as much as they execute ... You'll juggle a high-velocity mix of ownership across dbt models, Snowflake semantic layers, and ...

Analytics Engineer

New York, NY · Hybrid

$130K - $150K/yr

As an Analytics Engineer, you will play a crucial role in our organization, taking charge of ... Build and maintain dbt models across staging, intermediate, and mart layers following Kimball ...

Design, build, and maintain certified dbt models as the authoritative source for business-critical metrics. * Establish and enforce analytics engineering standards for modeling, testing ...

The fundamental role of the Analytics Engineer is to develop and maintain reusable data products ... Building data models in the data warehouse using dbt to support data analysis needs, consolidate ...

Showing results 21-40

Evening Analytics Engineer Dbt information

What is an evening analytics engineer dbt?

An Evening Analytics Engineer Dbt is a data professional who specializes in building and maintaining data transformation workflows using dbt (data build tool), typically working during evening hours. Their primary responsibilities include modeling raw data into clean, actionable datasets, ensuring data quality, and collaborating with data teams to provide reliable analytics. They often work with SQL, version control systems, and cloud data warehouses, ensuring that analytics pipelines run smoothly outside regular business hours. This role is ideal for organizations that require data engineering support during off-peak times or have distributed teams across multiple time zones.

How does working as an evening analytics engineer dbt typically impact collaboration with other teams?

As an Evening Analytics Engineer focused on dbt, you often work closely with data analysts, data scientists, and business stakeholders who rely on timely data transformations for their projects. The evening shift can mean you are responsible for monitoring and troubleshooting overnight data pipeline runs, ensuring data models are up-to-date for next-day use. This role requires proactive communication, detailed documentation, and sometimes handing off critical updates to colleagues starting their day shift. You may also participate in asynchronous meetings and use collaboration tools to stay aligned with the broader team’s goals and developments.

What are the key skills and qualifications needed to thrive as an evening analytics engineer dbt, and why are they important?

To thrive as an Evening Analytics Engineer (Dbt), you need strong data engineering skills, proficiency in SQL, and experience with data modeling, typically supported by a degree in computer science or a related field. Familiarity with dbt (data build tool), cloud data warehouses like Snowflake or BigQuery, and version control systems such as Git is essential. Strong problem-solving abilities, attention to detail, and effective communication are important soft skills for collaborating across teams and ensuring data accuracy. These skills are vital for building reliable data pipelines, enabling quality analytics, and supporting business decisions during evening or off-peak hours.

What is the difference between Evening Analytics Engineer Dbt vs Data Analyst?

AspectEvening Analytics Engineer DbtData Analyst
Primary FocusBuilding and maintaining data transformation pipelines using dbtAnalyzing data to generate reports and insights
Skills & ToolsSQL, dbt, data modeling, ETL processesSQL, Excel, visualization tools, reporting
Work EnvironmentData engineering teams, technical environment, often remoteBusiness teams, reporting environments, often in-office or hybrid
CredentialsSQL proficiency, data modeling knowledge, sometimes certifications in data engineeringStatistical or analytical degrees, SQL skills often required

While both roles involve working with data, the Evening Analytics Engineer Dbt focuses on building data pipelines and transformations using dbt, whereas the Data Analyst primarily interprets data to create reports and insights. The engineer role is more technical and engineering-oriented, while the analyst role emphasizes analysis and visualization.

What cities are hiring for Evening Analytics Engineer Dbt jobs?

Cities with the most Evening Analytics Engineer Dbt job openings:

What are the most commonly searched types of Analytics Engineer Dbt jobs?

The most popular types of Analytics Engineer Dbt jobs are:

What states have the most Evening Analytics Engineer Dbt jobs?

States with the most job openings for Evening Analytics Engineer Dbt jobs include:

What are popular job titles related to Evening Analytics Engineer Dbt jobs?

For Evening Analytics Engineer Dbt jobs, the most frequently searched job titles are:

Analytics Engineer II

Denver, CO • On-site

Other

Medical, Dental, Vision

Re-posted 22 days ago


Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Full-Time DENVER, CO, US

6 days ago Requisition ID: 3173

Join our growing team and discover why Summit Utilities, Inc. continues to earn national and regional recognition as an employer of choice. Our recognitions include Best Places to Work in Maine (2019–2025); Best Places to Work in Arkansas (2020, 2023, 2025); Best Places to Work in Oklahoma (2022–2025); Best Places to Work in Missouri (2023 and 2026); Best Places to Work in Colorado (2025); Forbes America’s Best Small Employers (2023); and, most recently, Proud and Purposeful Employer (2026).

Summit is a growing natural gas utility that’s committed to delivering reliable energy to homes and businesses in Arkansas, Colorado, Maine, Missouri, Oklahoma, and Texas. Being part of the Summit team means embracing excellence and innovation, committing to safety each and every day, and doing all that we can to serve each other, our customers, and the communities where we live. We aim to bring warmth and energy to everything we do.

We have an exciting hybrid opportunity for an Analytics Engineer II (SGL17) based in Denver, CO.

POSITION SUMMARY

Summit Utilities is seeking an Analytics Engineer II to design, develop, test, and maintain enterprise-grade analytics data products that power reporting, regulatory submissions, and operational decision-making across the company. Engineers at this level are expected to work independently on dbt model development within Microsoft Fabric and Azure SQL environments, owning specific subject areas (e.g., billing, AMI, SAP, customer) end-to-end – from source profiling through deployment and monitoring. This role is essential to delivering trustworthy, well-modeled, and well-tested datasets that bridge raw source data and business analytics. Ideal candidates bring 3–6 years of experience, proficiency in SQL and dbt, an understanding of data governance and metadata management, and the ability to translate analytical requirements into durable, well-documented data products.

PRIMARY DUTIES AND RESPONSIBILITIES

  • Design, build, and maintain dbt models that transform source data into governed, analytics-ready datasets across one or more subject areas.
  • Write and maintain dbt schema tests (not_null, unique, accepted_values, relationships) and source freshness checks to enforce data quality SLAs.
  • Optimize SQL transformations for performance, cost-efficiency (CU usage), and maintainability within Microsoft Fabric and Azure SQL environments.
  • Investigate root causes of data discrepancies across upstream and downstream systems, partnering with Data Engineers to remediate pipeline issues.
  • Gather and document data requirements from Data Analysts, business partners, and regulatory teams, translating them into dbt model designs.
  • Implement and maintain dbt project structure including refs, sources, YAML configs, packages (dbt_utils, dbt_expectations), and incremental materializations.
  • Author clear, business-friendly documentation in dbt’s documentation site, including model purpose, column definitions, and lineage notes.
  • Partner with Data Engineers on pipeline requirements and collaborate on shared standards for ingestion, modeling, and monitoring.
  • Contribute to source control and CI/CD workflows for dbt projects, including pull request review and deployment automation.
  • Support testing and validation for pipeline enhancements, schema changes, and source onboarding.
  • Mentor Analytics Engineer I peers through pair-programming, code review, and knowledge sharing.
  • Participate in team standups, sprint planning, code reviews, and architecture discussions.
  • Build working knowledge of utility data domains (billing, AMI, SCADA, SAP, GIS) and the data quality needs of each operational system.

EDUCATION AND WORK EXPERIENCE

  • Bachelor’s degree in data Analytics, Information Systems, Computer Science, Mathematics, or a related field preferred; equivalent combination of education and relevant experience will be considered.
  • 3–6 years of experience in analytics engineering, data engineering, data analysis, or BI development
  • Hands-on experience building and maintaining dbt models in a production or near-production environment.
  • Strong experience working with relational databases, including query writing, optimization, and stored procedure understanding.
  • Demonstrated experience working within cloud-based data environments (Microsoft Fabric, Azure SQL, AWS, or similar).
  • Familiarity with source control practices and CI/CD workflows for analytics or data projects.
  • Master’s degree in a quantitative field is preferred.

KNOWLEDGE, SKILLS, ABILITIES

  • Proficient SQL for querying, transformation, and analysis – comfortable with complex joins, CTEs, window functions, and subqueries
  • Working knowledge of dbt: ability to develop models, write schema tests, use packages, and understand refs and sources.
  • Solid understanding of ETL/ELT concepts and the data lifecycle from ingestion through consumption
  • Familiarity with data governance and metadata management practices
  • Ability to gather requirements, document assumptions, and translate analytical needs into dbt model designs.
  • Skilled at root cause analysis and triage across upstream and downstream systems
  • Working knowledge of cloud data platforms, with hands-on experience in Microsoft Fabric or Azure SQL preferred
  • Familiarity with API integrations, flat file ingestion (CSV, JSON, XML), and SAP data structures
  • Ability to work independently and own portions of project delivery from requirements through deployment.
  • Strong written documentation habits and ability to communicate technical decisions to teammates and stakeholders.
  • Proficiency with source control tools (Git, Azure DevOps, GitHub) and collaborative development practices
  • Working knowledge of natural gas distribution and utility data systems (billing, AMI, SCADA), and an understanding of data quality needs across operational systems
  • Friendly, solution-oriented team player aligned with Summit’s PEAKS values.

Salary based on experience $90K to $111K USD Annually

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and/or skills required of all personnel so classified.

Summit offers competitive pay and medical/dental/vision and other benefits that provide flexibility, choice, and support to our employees when they need it most. We understand that home and family are essential pieces of your life, and our benefits are designed to support you both at work and at home.

Summit Utilities, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or protected veteran status and will not be discriminated against on the basis of disability or veteran status .

#J-18808-Ljbffr