Bloomerang

Data Engineer

Rol remoto de Data Engineering con fit claro de ubicación del candidato.

Publicado23 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

Lead the end-to-end design, development, and implementation of enterprise data warehouse solutions supporting corporate analytics
Own the migration and refactor of Bloomerang’s data warehouse from Google BigQuery to Databricks, supporting all internal analytics use cases
Establish and maintain data warehouse standards, guidelines, and best practices across the organization
Design and build scalable ETL and ELT pipelines that ingest, transform, and integrate data from internal systems, including MySQL, PostgreSQL, Salesforce, and more
Work closely with analytics engineers to develop dimensional data models and enterprise data architecture that support reporting and business intelligence needs across the company
Partner with cross-functional stakeholders to translate business requirements into scalable, well-governed data solutions
Build automated data quality monitoring, validation, and governance processes to ensure accuracy and reliability of enterprise data
Optimize data warehouse performance, reliability, and cost across cloud environments
Create and maintain documentation for data architecture, pipelines, and data warehouse standards
Mentor team members and collaborate with engineering on data warehouse best practices

3-5 years of experience in data engineering or data warehouse development, ideally with experience leading enterprise data warehouse implementations
Hands-on experience migrating or working across modern cloud data warehouse platforms (e.g., BigQuery, Snowflake, Redshift); Databricks experience preferred
Expert-level SQL skills and strong data modeling capabilities for complex querying, transformation, and enterprise reporting
Experience with modern ETL and ELT tools and practices
Strong understanding of dimensional modeling, data warehouse design patterns (star and snowflake schema), and enterprise data architecture
Experience establishing data governance, standards, and best practices for agrowing organization
Proficiency in Python or similar programming languages for data pipelinedevelopment
Experience integrating with core business systems and APIs, including Salesforce,MySQL, and PostgreSQL
Familiarity with cloud platforms (preferably Google Cloud Platform) and moderndata stack tools
Experience with version control, CI/CD practices, and collaborative developmentworkflows
Strong analytical and problem-solving skills with close attention to data qualityand accuracy
Excellent communication skills and the ability to lead cross-functional collaboration in a fast-paced, growing organization
Experience working in a SaaS or technology company is a plus, but not required

Roles similares