1 to 25 of 56 Remote dbt Jobs

ability (Vue, React or Angular good but not necessary) Agile The following is DESIRABLE, not essential: AWS or GCP Buy-side Data tools such as Glue, Athena, Airflow, Ignite, DBT, Arrow, Iceberg, Dremio Fixed Income performance, risk or attribution TypeScript and Node Role: Python Developer (Software Engineer Programmer Developer Python Fixed Income JavaScript Node Fixed Income Credit Rates Bonds ABS … to be in the office 1-2 times a week. The tech environment is very new and will soon likely include exposure to the following: Glue, Athena, Airflow, Ignite, DBT, Arrow, Iceberg, Dremio This is an environment that has been described as the only corporate environment with a start-up/fintech attitude towards technology. Hours are 9-5. More ❯

to know it today but to learn from the team as it makes up a large part of the stack). Good knowledge of Data Engineering tooling such as dbt or Spark. CDC tools like Debezium are a bonus. Build data systems with a software and infrastructure engineer mindset, including tested, scalable, resilient, fault tolerant, observable and "as code" practices. More ❯

practices around CI/CD, infrastructure-as-code, and modern data tooling Introduce and advocate for scalable, efficient data processes and platform enhancements Tech Environment: Python, SQL, Spark, Airflow, dbt, Snowflake, Postgres AWS (S3), Docker, Terraform Exposure to Apache Iceberg, streaming tools (Kafka, Kinesis), and ML pipelines is a bonus What We're Looking For: 5+ years in Data Engineering More ❯

time and analytical data pipelines, metadata, and cataloguing (e.g., Atlan) Strong communication, stakeholder management, and documentation skills Preferred (but not essential): AWS or Snowflake certifications Knowledge of Apache Airflow, DBT, GitHub Actions Experience with Iceberg tables and data product thinking Why Apply? Work on high-impact, high-scale client projects Join a technically elite team with a strong culture of More ❯

Key Responsibilities: Design and maintain scalable data pipelines across diverse sources including CMS, analytics, ad tech, and social platforms. Lead engineering efforts to automate workflows using tools like Airflow, dbt, and Spark. Build robust data models to support dashboards, A/B testing, and revenue analytics. Collaborate with cross-functional teams to deliver actionable insights and support strategic initiatives. Drive More ❯

Key Responsibilities: Design and maintain scalable data pipelines across diverse sources including CMS, analytics, ad tech, and social platforms. Lead engineering efforts to automate workflows using tools like Airflow, dbt, and Spark. Build robust data models to support dashboards, A/B testing, and revenue analytics. Collaborate with cross-functional teams to deliver actionable insights and support strategic initiatives. Drive More ❯

Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure to DBT, Docker, or Microsoft BI stack is a plus. What’s on offer: Opportunity to work on large-scale, high-impact data projects. A collaborative, supportive environment with scope to grow More ❯

Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure to DBT, Docker, or Microsoft BI stack is a plus. What’s on offer: Opportunity to work on large-scale, high-impact data projects. A collaborative, supportive environment with scope to grow More ❯

for a Data Engineer to join their London-based team. Key Responsibilities: Design and maintain scalable data pipelines across diverse sources. Automate and optimise workflows using tools like Airflow, dbt, and Spark. Support data modelling for analytics, dashboards, and A/B testing. Collaborate with cross-functional teams to deliver data-driven insights. Work with cloud platforms (GCP preferred) and More ❯

for a Data Engineer to join their London-based team. Key Responsibilities: Design and maintain scalable data pipelines across diverse sources. Automate and optimise workflows using tools like Airflow, dbt, and Spark. Support data modelling for analytics, dashboards, and A/B testing. Collaborate with cross-functional teams to deliver data-driven insights. Work with cloud platforms (GCP preferred) and More ❯

day a week in a central London office High-growth scale-up with a strong mission and serious funding Modern tech stack: Python, SQL, Snowflake, Apache Iceberg, AWS, Airflow, dbt, Spark Work cross-functionally with engineering, product, analytics, and data science leaders What You'll Be Doing Lead, mentor, and grow a high-impact team of data engineers Define and More ❯

e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience designing and building data lakes and modern data platforms. Proficiency with Python, SQL, and data pipeline orchestration tools (e.g., Airflow, dbt). Strong understanding of data modelling, ETL/ELT processes, and distributed systems. Knowledge of data security, governance, and compliance best practices. Excellent leadership, communication, and stakeholder engagement skills. What More ❯

data solutions Proficiency in Python, SQL, and data modelling tools (e.g. Erwin, Lucidchart) Strong knowledge of AWS services (Lambda, SNS, S3, EKS, API Gateway) Familiarity with Snowflake, Spark, Airflow, DBT, and data governance frameworks Preferred: Certifications in cloud/data technologies Experience with API/interface modelling and CI/CD (e.g. GitHub Actions) Knowledge of Atlan and iceberg tables More ❯

Tech Lead, Data Engineering Manager etc. Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Experience building, defining, and owning data models, data lakes, and data warehouses Programming proficiency in Python, Pyspark, Scala or Java. Experience operating in a cloud-native environment (e.g. More ❯

Tech Lead, Data Engineering Manager etc. Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Experience building, defining, and owning data models, data lakes, and data warehouses Programming proficiency in Python, Pyspark, Scala or Java. Experience operating in a cloud-native environment (e.g. More ❯

Tech Lead, Data Engineering Manager etc. Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Experience building, defining, and owning data models, data lakes, and data warehouses Programming proficiency in Python, Pyspark, Scala or Java. Experience operating in a cloud-native environment (e.g. More ❯

Strong technical background (5+ years) in building scalable data platforms Excellent communication and stakeholder management skills Hands-on experience with modern data tools and technologies — Python, SQL, Snowflake, Airflow, dbt, Spark, AWS, Terraform A collaborative mindset and a passion for mentoring and developing others Comfortable balancing technical decisions with business needs Nice to have: experience with Data Mesh, real-time More ❯

solutions. You'll work closely with senior engineers and stakeholders, supporting data pipeline development and helping improve data accessibility. Key Responsibilities Assist in building and maintaining data pipelines using dbt and Snowflake, ensuring they are scalable and efficient. Collaborate with analytics engineers and stakeholders across Product, Marketing, and Analytics teams to support data needs. Contribute to BI tool adoption and More ❯

Azure ecosystem. Required Experience: Creating mapping specifications between legacy and CRM, ERP, Finance applications Integration to D365, Dataverse solutions or other SaaS applications Data Quality Frameworks: Soda.io, Great Expectations, DBT Creation of fault-tolerant data ingestion pipelines in SSIS/KWS/Data Factory/data flows using Linked Services, Integration Datasets Extracting data from a variety of sources including More ❯

Tech Lead, Data Engineering Manager etc. Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Experience building, defining, and owning data models, data lakes, and data warehouses Programming proficiency in Python, Pyspark, Scala or Java. Experience operating in a cloud-native environment (e.g. More ❯

platforms (e.g. Databricks, Azure, AWS or GCP native stacks)Experience with platform observability and CI/CD for data platformsHands-on experience with modern data engineering tools such as dbt, Fivetran, Matillion or AirflowHistory of supporting pre-sales activities in a product or consultancy-based businessWhat Kubrick offers:We are a fast moving and fast growth business which is doing More ❯

with architects, analysts, and business stakeholders to unlock insights and enable innovation. What You'll Be Doing: Design and build robust, automated data pipelines using Azure Data Factory, Synapse, dbt, and Databricks. Integrate data from enterprise systems (e.g. Dynamics, iTrent, Unit4) into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI More ❯

with architects, analysts, and business stakeholders to unlock insights and enable innovation. What You'll Be Doing: Design and build robust, automated data pipelines using Azure Data Factory, Synapse, dbt, and Databricks. Integrate data from enterprise systems (e.g. Dynamics, iTrent, Unit4) into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI More ❯

with architects, analysts, and business stakeholders to unlock insights and enable innovation. What You'll Be Doing: Design and build robust, automated data pipelines using Azure Data Factory, Synapse, dbt, and Databricks. Integrate data from enterprise systems (e.g. Dynamics, iTrent, Unit4) into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI More ❯

with architects, analysts, and business stakeholders to unlock insights and enable innovation. What You'll Be Doing: Design and build robust, automated data pipelines using Azure Data Factory, Synapse, dbt, and Databricks. Integrate data from enterprise systems (e.g. Dynamics, iTrent, Unit4) into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI More ❯