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Coalesce Jobs (NOW HIRING)

Analyze existing Coalesce.io pipelines and Snowflake tables to understand current data flows and logic * Translate business requirements into clear, structured documentation (e.g., data requirements ...

Analyze existing Coalesce.io pipelines and Snowflake tables to understand current data flows and logic * Translate business requirements into clear, structured documentation (e.g., data requirements ...

Analyze existing Coalesce.io pipelines and Snowflake tables to understand current data flows and logic * Translate business requirements into clear, structured documentation (e.g., data requirements ...

Data Analyst

Jericho, NY · On-site

$90K - $110K/yr

Analyze existing Coalesce.io pipelines and Snowflake tables to understand current data flows and logic * Translate business requirements into clear, structured documentation (e.g., data requirements ...

Experience with Coalesce or similar transformation frameworks * Experience with data warehousing (Snowflake) * Experience modeling complex datasets (fact/dimension modeling, star schemas)

Data Analytics Engineer

Fort Collins, CO · On-site

$102K - $146.90K/yr

Experience with Coalesce or similar transformation frameworks * Experience with data warehousing (Snowflake) * Experience modeling complex datasets (fact/dimension modeling, star schemas)

Sr. Business Intelligence Analyst

Rosemont, IL · On-site

$109.40K - $153.80K/yr

Design, build, and maintain data pipelines using Azure Data Factory, Coalesce.io, and Snowflake to load, transform, and integrate data into the data warehouse, ensuring scalability, accurate, and ...

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How much do coalesce jobs pay per year?

As of May 30, 2026, the average yearly pay for coalesce in the United States is $82,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $85,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer using Coalesce, and why are they important?

To thrive as a Data Engineer using Coalesce, you need expertise in data modeling, ETL/ELT processes, and proficiency with SQL, often supported by a degree in computer science or related fields. Familiarity with the Coalesce platform, cloud data warehouses (like Snowflake), and relevant certifications in data engineering are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with teams and troubleshoot complex data issues. These skills are crucial for efficiently designing, optimizing, and maintaining robust data pipelines that support organizational analytics and decision-making.

What are some common challenges faced by data engineers working with Coalesce, and how can they be addressed?

Data engineers using Coalesce often face challenges related to integrating complex data sources and maintaining data quality as pipelines scale. Collaboration with cross-functional teams, such as analysts and data scientists, is essential to ensure that transformations meet business requirements. Staying current with platform updates and best practices helps address evolving architectural needs, while routine documentation and modular pipeline design can streamline troubleshooting and onboarding. Leveraging Coalesce's visual interface and automation features can also reduce manual errors and improve overall workflow efficiency.

What are Coalesce jobs?

Coalesce jobs typically refer to roles at Coalesce, a data transformation platform designed to help organizations automate and streamline their data workflows. Employees at Coalesce may work in areas such as software development, data engineering, customer support, and product management. These jobs often involve building, maintaining, or supporting tools that help users transform, organize, and analyze large datasets efficiently. Working at Coalesce usually requires strong technical skills, a good understanding of modern data architectures, and an interest in solving data-related challenges.

What is the difference between Coalesce vs Data Analyst?

AspectCoalesceData Analyst
Required CredentialsTypically SQL certifications, data management skillsDegree in statistics, data science, or related field; SQL knowledge
Work EnvironmentData management teams, database environmentsBusiness environments, analytics teams
Employer & Industry UsageUsed in database administration, data warehousingUsed across industries for data interpretation and reporting

While Coalesce is a function used in SQL to handle null values, Data Analysts focus on interpreting data to inform business decisions. Both roles require SQL skills, but Coalesce is a technical function, whereas Data Analysts perform broader data analysis tasks.

More about Coalesce jobs
What cities are hiring for Coalesce jobs? Cities with the most Coalesce job openings:
What states have the most Coalesce jobs? States with the most job openings for Coalesce jobs include:
Infographic showing various Coalesce job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, 2% Part Time, 1% Temporary, and 3% Contract. Highlights an 66% Physical, 23% Hybrid, and 11% Remote job distribution, with an average salary of $82,013 per year, or $39.4 per hour.
Data Analyst

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

We are seeking a technically strong and detail-oriented Data Analyst to join our Business Intelligence team. This role is ideal for someone who excels at bridging the gap between business needs and data solutions.

In this role, you will work closely with business stakeholders to gather and clarify requirements, analyze existing data pipelines (built in Coalesce.io), and translate business needs into clear, structured documentation for development teams. You will play a key role in ensuring data products are well-defined, consistent, and aligned with business objectives.

This is not a development role - it is focused on analysis, documentation, and data product definition, with strong technical context.

What You'll Do

  • Partner with business stakeholders to gather, clarify, and document data and reporting requirements
  • Analyze existing Coalesce.io pipelines and Snowflake tables to understand current data flows and logic
  • Translate business requirements into clear, structured documentation (e.g., data requirements, transformation logic, mapping specs) for data engineering teams
  • Define and document business metrics, KPIs, and data definitions to ensure consistency across reporting and analytics
  • Work with data engineers to validate that delivered solutions meet documented requirements
  • Support the developers by ensuring requirements are complete, accurate, and well understood
  • Identify gaps, inconsistencies, or data quality issues in existing pipelines and propose improvements
  • Contribute to data governance efforts by maintaining documentation and promoting best practices

What We're Looking For

Required Qualifications

  • 3-5 years of experience in data analytics, analytics engineering, or data engineering roles.
  • Strong SQL skills and experience working with Snowflake or similar cloud data warehouses.
  • Exposure to ELT pipelines and tools such as Coalesce.io, dbt, or comparable frameworks.
  • Experience supporting BI and analytics tools such as Sigma, Power BI, Tableau, or Looker.
  • Solid understanding of data modeling concepts (e.g., star schemas, fact and dimension tables).
  • Ability to work directly with business users and translate requirements into data solutions.
  • Experience with data documentation and data catalogs
  • Exposure to data quality ideologies and data governance practices
  • Experience supporting analytics and reporting use cases

Why Join Us

  • Be part of a modern data organization focused on data as a product.
  • Work with a contemporary analytics stack including Snowflake, Coalesce.io, Sigma, and Power BI.
  • Opportunity to grow your skills across both analytics and data engineering.
  • High visibility role with meaningful impact on how the business uses data.