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Coalesce Jobs (NOW HIRING)

Colgate-Palmolive

Data Architect

Piscataway, NJ · On-site

$63.75 - $82/hr

... Coalesce • Knowledge of data warehousing/data lakes (e.g., Databricks, GCP BigQuery, Hadoop) • Understanding of modeling methodologies (relational, dimensional, NoSQL) and integration patterns ...

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$85.5K

How much do coalesce jobs pay per year?

As of Jul 13, 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 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.

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.
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:
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Coalesce jobs near you
Infographic showing various Coalesce job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $82,013 per year, or $39.4 per hour.
Data Engineering Manager II - Denver

Data Engineering Manager II - Denver

Wilbur-Ellis

Denver, CO • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Wilbur-Ellis is a 100-year-old family-owned leader in agriculture, investing heavily in employee development and fostering a supportive work environment. The Data Engineering Manager II will lead the design and operation of enterprise data platforms and AI-enabled solutions, overseeing a team and collaborating with various stakeholders to deliver scalable data and AI solutions.
Responsibilities:
• Lead the data and AI engineering solutions team of 5–10 people with a clear strategic vision aligned to enterprise data, development, and AI roadmaps.
• Partner with business and functional leaders to identify high-value data engineering, development, and AI opportunities.
• Oversee the development and operation of cloud-based data ingestion, data lake, and data warehouse solutions.
• Participate in the AI Center of Excellence (CoE) to define standards, patterns, and governance for data engineering, analytics, and AI solutions.
• Guide the team across the full lifecycle from requirements and architecture through development, testing, deployment, and support.
• Provide technical leadership for Snowflake-based data platforms and associated analytics layers.
• Lead CI/CD practices for data engineering using Azure DevOps and Agile methodologies; manage sprint planning and execution.
• Drive adoption of AI-enabled capabilities, including advanced analytics, machine learning models, and generative AI solutions where appropriate.
• Ensure data and AI solutions meet security, privacy, governance, and compliance standards.
• Monitor emerging data and AI trends and evaluate their applicability to the organization.
• Build and maintain strong relationships with business leaders, stakeholders, and cross-functional technology teams.
Qualifications:
Required:
• 5+ years of experience in a developer or data engineering role, with strong exposure to the software development lifecycle (SDLC) and data platform delivery
• 5+ years of experience leading and developing technical teams, with a background in cloud data platform design, development, and implementation
• 7+ years of experience with DW/BI and cloud data technologies (Snowflake strongly preferred)
• Strong expertise in data modeling, including conceptual, logical, and dimensional (star/snowflake) schemas
• Advanced SQL skills for analyzing and interpreting enterprise-scale datasets
• Deep understanding of relational databases, data warehousing patterns, and source system integration
• Understanding of generative AI use cases for analytics, data productivity, and business workflows (e.g., copilots, natural language querying, summarization)
• Experience delivering AI/ML-enabled data products, such as predictive models, forecasting, recommendations, anomaly detection, or intelligent automation
• Experience supporting self-service analytics, semantic layers, and data consumption tools
• Strong understanding of data governance concepts including data quality, metadata management, data catalogs, and master data management
• Skills in ELT/ETL and orchestration tools (e.g., Fivetran, Coalesce, dbt, Airflow or equivalents)
• Experience with Agile delivery methodologies
• Bachelor’s degree in a related discipline or equivalent experience
Company:
Wilbur-Ellis specializes in the marketing and distribution of agricultural products, animal nutrition, and specialty chemicals. Founded in 1921, the company is headquartered in San Francisco, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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