Find Your Next Analytics Engineering Job

A curated list of analytics engineering job openings with details intelligently extracted by AI.

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  • Data analysis and modeling to solve business problems
  • Translate business needs into analytical questions and build end-to-end analytical solutions
  • Communicate findings and recommendations to stakeholders
  • Develop and maintain data pipelines and infrastructure
Posted Aug 1, 2025
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  • Data Architecture
  • Data Modeling
  • ETL/ELT Development
  • Cloud Data Platform Implementation
  • Data Governance
Posted Aug 1, 2025
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  • Develop and maintain data pipelines.
  • Build data models and ETL processes.
  • Design and implement data analytics solutions.
  • Collaborate with stakeholders to understand data needs.
  • Ensure data quality and accuracy.
Posted Aug 1, 2025
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  • Develop and maintain data pipelines.
  • Build data models and schemas in cloud data warehouse.
  • Collaborate with other teams to understand data needs.
  • Monitor and troubleshoot data pipeline performance.
  • Implement data quality checks and monitoring.
Posted Jul 30, 2025
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  • Develop and maintain data pipelines and ETL processes.
  • Design and implement data models and data warehouses.
  • Collaborate with stakeholders to understand data needs and translate them into technical solutions.
  • Ensure data quality and accuracy through data validation and testing.
  • Utilize cloud-based data platforms and services.
Posted Jul 30, 2025
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  • Develop and maintain data pipelines and ETL processes.
  • Design, develop, and maintain data models.
  • Collaborate with business users to gather requirements and translate them into technical specifications.
  • Perform data analysis and quality assurance to ensure data accuracy and integrity.
  • Develop and maintain documentation for data processes and systems.
Posted Jul 29, 2025
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  • Design, develop, and maintain data pipelines and ETL workflows to ingest, transform, and load data from various sources into our data warehouse.
  • Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and translate them into technical solutions.
  • Build and maintain data models and data dictionaries to ensure data consistency and quality.
  • Develop and maintain data quality monitoring and alerting systems to identify and resolve data issues.
  • Stay up-to-date with the latest trends and technologies in data engineering and advanced analytics.
Posted Jul 28, 2025
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  • Develop and maintain data pipelines.
  • Design and implement data models.
  • Collaborate with stakeholders to understand data needs.
  • Ensure data quality and accuracy.
  • Automate data processes.
Posted Jul 27, 2025
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  • Develop and maintain data pipelines using tools like dbt and Python.
  • Design and build data models in cloud data warehouses such as Snowflake.
  • Collaborate with stakeholders to gather requirements and translate them into technical solutions.
  • Implement data quality checks and monitoring to ensure data accuracy and reliability.
Posted Jul 25, 2025
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  • Develop and maintain data models and pipelines to enable data-driven decision-making.
  • Collaborate with cross-functional teams to understand data needs and translate them into technical solutions.
  • Build and maintain data documentation, data dictionaries, and data lineage to ensure data quality and accessibility.
  • Optimize data pipelines and data models for performance, scalability, and reliability.
Posted Jul 24, 2025
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  • Build data pipelines to ingest data from various sources into the cloud data warehouse.
  • Develop data models and transformations using dbt to support business requirements.
  • Collaborate with stakeholders to understand data needs and translate them into technical solutions.
  • Implement data quality checks and monitoring to ensure data accuracy and reliability.
  • Optimize data pipelines and queries for performance and scalability.
Posted Jul 24, 2025
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  • Design, build, and maintain data pipelines using Python, SQL, and Airflow.
  • Develop data models and schemas in Snowflake.
  • Collaborate with data scientists and business analysts to understand data requirements.
  • Implement data quality checks and monitoring.
  • Optimize data pipelines for performance and scalability.
Posted Jul 23, 2025
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  • Develop and maintain data pipelines for pricing optimization.
  • Collaborate with data scientists and business stakeholders.
  • Ensure data quality and reliability.
  • Apply analytics to improve pricing strategies.
Posted Jul 23, 2025
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  • Data lake ecosystem design and implementation
  • Data governance and security
  • ETL pipeline development and maintenance
  • Collaboration with stakeholders to understand data needs
  • Performance optimization of data systems
Posted Jul 23, 2025
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  • Data collection, integration, and modeling from manufacturing operations data sources
  • Develop and maintain data pipelines using cloud-based data engineering tools
  • Collaborate with cross-functional teams to define data requirements and deliver data-driven solutions
  • Develop data visualizations and dashboards to monitor key performance indicators (KPIs) and identify areas for improvement
  • Ensure data quality and accuracy through data validation and testing
Posted Jul 23, 2025
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  • Design, develop, and maintain data pipelines using cloud-based technologies to support data transformation, data structures, metadata, dependency and workload management.
  • Develop and implement data models, schemas, and ETL processes to support data warehousing and business intelligence needs.
  • Ensure data quality and integrity by implementing data validation rules, monitoring data pipelines, and resolving data issues.
  • Collaborate with cross-functional teams to understand data requirements and provide data solutions that meet business needs.
  • Stay current with emerging data technologies and trends and make recommendations for new technologies and approaches to improve data management and analytics.
Posted Jul 22, 2025
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  • Data analysis and problem-solving
  • Data visualization and presentation
  • Collaboration with cross-functional teams
  • Data manipulation and transformation
  • Data quality and governance
Posted Jul 22, 2025
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  • Data Pipelines: Design, develop, and maintain robust data pipelines.
  • Data Modeling: Create and optimize data models.
  • Stakeholder Collaboration: Work closely with stakeholders to understand their requirements.
  • BI Solutions: Develop insightful BI solutions and reporting dashboards.
  • Data Quality: Ensure data accuracy and reliability.
Posted Jul 22, 2025
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  • Develop and maintain data pipelines and ETL processes.
  • Collaborate with business partners to understand data requirements.
  • Design and implement data models and reporting solutions.
  • Ensure data quality and accuracy.
  • Utilize analytical and data visualization tools
Posted Jul 22, 2025
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  • Design, develop, and maintain scalable data pipelines using Snowflake, dbt, and Python.
  • Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
  • Build and maintain data models and transformations to support business intelligence and analytics.
  • Monitor data quality and performance, identifying and resolving issues proactively.
  • Contribute to the development of data engineering best practices and standards.
Posted Jul 21, 2025
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  • Develop, implement, and maintain data pipelines using various tools and technologies.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Apply data mining and machine learning techniques to extract insights and develop predictive models.
  • Ensure data quality and integrity by implementing data validation and monitoring processes.
Posted Jul 21, 2025
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