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Evening Analytics Engineer Dbt Jobs (NOW HIRING)

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 ...

You'll spend roughly half your time on dbt model development and half on Tableau dashboard delivery and business stakeholder engagement - the bridge between our Analytics Engineering platform and the ...

The Analytics Engineer will play a critical role in transforming raw data into trusted, analytics ... Implement dbt tests, documentation, and exposures to improve data quality, observability, and ...

Data Modeling & Analytics Engineering • Design, build, and maintain analytics ready data models using dbt, following dimensional and semantic modeling best practices (e.g., star schemas, marts ...

Required * 5+ years of analytics engineering or data analyst experience, with at least 3 years hands-on with dbt (Core or Cloud) - building and maintaining multi-layer model architectures in a ...

Posted today

You'll spend roughly half your time on dbt model development and half on Tableau dashboard delivery and business stakeholder engagement - the bridge between our Analytics Engineering platform and the ...

... dbt models: builds, tests, and documents staging, intermediate, and mart models that serve as the ... in analytics engineering, data engineering, or a data analyst role that included dbt and data ...

Required : • 3+ years of experience in analytics engineering, data analytics, or a hybrid data role • Deep expertise in SQL and dbt • Experience with BigQuery or comparable cloud data ...

TITLE: Senior Analytics Engineer EMPLOYER: ID.me, LLC (formerly known as: ID.me, Inc.) LOCATION ... Support our data infrastructure which includes Snowflake, dbt, Sigma, and GCP services. Educate the ...

About the Role We are looking for an experienced Analytics Engineer to own and evolve the BI team's technical infrastructure (Snowflake, dbt, GitLab CI/CD, scheduling frameworks, and ingestion ...

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 are seeking an Analytics Engineer to design and build our DBT analytics infrastructure from the ground up. This is a greenfield opportunity for someone who has done it before and knows exactly how ...

We are seeking an Analytics Engineer to design and build our DBT analytics infrastructure from the ground up. This is a greenfield opportunity for someone who has done it before and knows exactly how ...

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 ...

New

We are seeking an Analytics Engineer to design and build our DBT analytics infrastructure from the ground up. This is a greenfield opportunity for someone who has done it before and knows exactly how ...

They are hiring an Analytics Engineer II to focus on building and maintaining scalable data models ... Responsibilities : • Develop, optimize, and maintain dbt models across WHOOP's Snowflake data ...

New

As an Analytics Engineer, you will play a crucial role in driving data-driven decision making ... Create tests for dbt models to ensure data quality and manage our daily dbt runs (via dbt Cloud)

As an Analytics Engineer, you will play a crucial role in driving data-driven decision making ... Create tests for dbt models to ensure data quality and manage our daily dbt runs (via dbt Cloud)

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Evening Analytics Engineer Dbt information

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.

How does working as an Evening Analytics Engineer specializing in 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 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.

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 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:

Data Engineer (DBT Specialist)

ACS Consultancy Services

Albany, NY • Remote

$117K - $140K/yr

Other

Re-posted 16 days ago


Job description

Job Title: Data Engineer (DBT Specialist)

Location: Remote

We are currently seeking candidates who meet the following qualifications.

Key Responsibilities

  • Design and implement scalable data models and transformation pipelines using DBT (Data Build Tool).
  • Build and maintain ELT workflows using tools like Airflow, Fivetran, or custom Python scripts.
  • Work with data warehouses such as Snowflake, BigQuery, or Redshift to optimize storage and performance.
  • Ensure data quality, governance, and consistency through testing, version control, and documentation in DBT.
  • Collaborate with analysts and stakeholders to understand data needs and deliver efficient, reusable models.
  • Monitor pipeline performance and troubleshoot issues across the data stack.
  • Implement and maintain CI/CD practices for analytics engineering.
  • Stay up-to-date with best practices in data modeling, pipeline architecture, and cloud data tools.
Requirements
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
  • Experience in data engineering or analytics engineering roles.
  • Strong hands-on experience with DBT in production environments.
  • Solid understanding of SQL and data warehousing principles.
  • Experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift).
  • Experience with Python or another scripting language for ETL/ELT tasks.
  • Experience with orchestration tools like Airflow, Prefect, or Dagster.
  • Git proficiency for version control and collaboration.
  • Strong communication and collaboration skills.
  • Federal Experience is a plus.
  • Required Security clearance.
    If you meet these qualifications, please submit your application via link provided in Linkedin.
    Kindly do not call the general line to submit your application.