1 to 25 of 342 Remote Snowflake Jobs

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

environments (AWS, GCP, or Azure), infrastructure-as-code practices, and ideally container orchestration with Kubernetes. Familiarity with SQL and NoSQL databases (Cassandra, Postgres), ideally combined with data collaboration platforms (Snowflake, Databricks) Strong DevOps mindset with experience in CI/CD pipelines, monitoring, and observability tools (Grafana or equivalent). Exposure to analytics, reporting, and BI tools such as Apache Superset More ❯

time streaming architectures, to support advanced analytics, AI, and business intelligence use cases. Proven experience in designing architectures for structured, semi-structured, and unstructured data , leveraging technologies like Databricks, Snowflake, Apache Kafka , and Delta Lake to enable seamless data processing and analytics. Hands-on experience in data integration , including designing and optimising data pipelines (batch and streaming) and integrating cloud More ❯

level and translating requirements into solution blueprints, proposals, and presentations. Enterprise Solution Design – Architect end-to-end data and cloud solutions across platforms such as Azure, AWS, GCP, Databricks, Snowflake, Synapse, or Azure Fabric. Cloud Strategy & Adoption – Define and lead cloud migration, modernisation, and optimisation strategies using tools such as Terraform, Azure DevOps, and CI/CD pipelines. Data Products More ❯

level and translating requirements into solution blueprints, proposals, and presentations. Enterprise Solution Design – Architect end-to-end data and cloud solutions across platforms such as Azure, AWS, GCP, Databricks, Snowflake, Synapse, or Azure Fabric. Cloud Strategy & Adoption – Define and lead cloud migration, modernisation, and optimisation strategies using tools such as Terraform, Azure DevOps, and CI/CD pipelines. Data Products More ❯

reporting. Key Experience and Skills Proven experience delivering large-scale data migration or data replatforming projects, ideally moving from SQL to Google Cloud or BigQuery (or equivalent, such as Snowflake or Redshift). Strong understanding of data warehousing concepts, including ETL/ELT, schema design, data modelling, and validation. Experience working with BI tools such as Power BI, Looker, or More ❯

role. Experience using SQL and Python to effectively automate data pipelines and other tasks with tools such as dbt, airflow. Strong experience with data lakehouse architecture (e.g DataBricks,Redshift, Snowflake, BigQuery). Exposure to cloud services and their configuration (e.g AWS). Experience in building and documenting data architectures and ETL/ELT processes, with a strong emphasis on performance More ❯

role. Experience using SQL and Python to effectively automate data pipelines and other tasks with tools such as dbt, airflow. Strong experience with data lakehouse architecture (e.g DataBricks,Redshift, Snowflake, BigQuery). Exposure to cloud services and their configuration (e.g AWS). Experience in building and documenting data architectures and ETL/ELT processes, with a strong emphasis on performance More ❯

s degree in Computer Science, Information Technology, or related field. Experience with the following: PowerBI Governance Framework PowerBI vendor and stakeholder management Ideally, you will also have: Experience with Snowflake, Tableau, and other BI tools is a plus. Knowledge of Specialty Insurance domain is advantageous. What we look for You are detail-oriented, proactive, and thrive in a fast-paced More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

teams to resolve them. Strong analytical mindset and attention to detail. Clear, concise communicator able to present technical findings simply. Desirable: Experience testing in big data environments using Databricks, Snowflake, or Redshift. Knowledge of data governance and lineage tracking tools. Exposure to data performance and load testing. Experience in an Agile delivery environment. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Engineer or in a similar data engineering/BI role Advanced SQL skills with hands-on experience using dbt for data modeling Strong familiarity with modern data platforms like Snowflake, Looker, AWS/GCP, Tableau, or Airflow Experience with version control tools (e.g., Git) Ability to design, build, and document scalable, reliable data models Comfortable gathering business requirements and translating More ❯

/uplifted/improving Conceptual Data Models) Strong knowledge of MS Azure stack (including Data Factory (ADF), Data Lake Storage, SQL, Azure ML and Power BI) Proven experience with Snowflake Architecture, including DevOps integration and CI/CD practices Advocate for positive personal participation in workshops, and demonstrate critical thinking on key topics Previous experience with large, Enterprise scale Data More ❯

/uplifted/improving Conceptual Data Models) Strong knowledge of MS Azure stack (including Data Factory (ADF), Data Lake Storage, SQL, Azure ML and Power BI) Proven experience with Snowflake Architecture, including DevOps integration and CI/CD practices Advocate for positive personal participation in workshops, and demonstrate critical thinking on key topics Previous experience with large, Enterprise scale Data More ❯

position management. Leverage AWS cloud technologies (including ECS, Lambda, S3, and CloudWatch) to deploy scalable, high-availability systems for data processing and analytics. Integrate and optimize data pipelines with Snowflake, enabling efficient access to large-scale market and transactional data. Build and deploy cloud-native systems that seamlessly integrate with front-office platforms powering real-time analytics, visualization, and decision More ❯

position management. Leverage AWS cloud technologies (including ECS, Lambda, S3, and CloudWatch) to deploy scalable, high-availability systems for data processing and analytics. Integrate and optimize data pipelines with Snowflake, enabling efficient access to large-scale market and transactional data. Build and deploy cloud-native systems that seamlessly integrate with front-office platforms—powering real-time analytics, visualization, and decision More ❯