1 to 25 of 158 Remote dbt Jobs

experience building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and 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 ❯

an Agile environment. Technical Proficiency: Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (Kafka, Flink, DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. CI/CD: Detailed understanding of working automated More ❯

Alerting: Prometheus, Datadog, Pagerduty Telemetry Standards: OpenTelemetry Application & Data Ecosystem (Supporting): Application Languages/Frameworks: Python, FastAPI, Flask, Node.js, React Data Streaming: Apache Kafka Data Processing/Transformation: Pandas, DBT Workflow Orchestration: Apache Airflow, Ray Machine Learning Stack: Serving: Triton Inference Server MLOps/Experiment Tracking: Weights and Biases, DVC Libraries/Frameworks: Transformers, HuggingFace Model Optimization/Formats: Onnx More ❯

needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL and Python (or another More ❯

needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL and Python (or another 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 ❯

experience in data engineering or a related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT pipelines . Proficiency in SQL More ❯

love to talk to you if: You've led technical delivery of data engineering projects in a consultancy or client-facing environment You're experienced with Python, SQL, .NET, dbt, Airflow and cloud-native data tools (AWS, GCP or Azure) You have strong knowledge of data architecture patterns - including Lakehouse and modern warehouse design (e.g. Snowflake, BigQuery, Databricks) You know More ❯

data pipelines, and ETL processes Hands-on experience with cloud platforms (GCP, AWS, Azure) and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex More ❯

Our products are recognised by industry leaders like Gartner's Magic Quadrant, Forrester Wave and Frost Radar. Our tech stack: Superset and similar data visualisation tools. ETL tools: Airflow, DBT, Airbyte, Flink, etc. Data warehousing and storage solutions: ClickHouse, Trino, S3. AWS Cloud, Kubernetes, Helm. Relevant programming languages for data engineering tasks: SQL, Python, Java, etc. What you will be More ❯

data pipelines, and ETL processes Hands-on experience with cloud platforms (GCP, AWS, Azure) and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and More ❯

Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and More ❯

Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness 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 ❯

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 ❯

and operating data pipelines, warehouses, and scalable data architectures. Deep hands-on experience with modern data stacks. Our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform. Experience with similar technologies is essential. Coaching & Growth Mindset: Passion for developing others through mentorship, feedback, and knowledge sharing. Pragmatic Problem More ❯

and operating data pipelines, warehouses, and scalable data architectures. Deep hands-on experience with modern data stacks. Our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform. Experience with similar technologies is essential. Coaching & Growth Mindset: Passion for developing others through mentorship, feedback, and knowledge sharing. Pragmatic Problem More ❯

office once a week . Requirements: Proven experience as an Analytics 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 More ❯

building LLM powered conversational systems in a software product setting. Comfortable with SQL, preferably with an enterprise database system like Redshift, Postgres. Ideally experience with data processing tools like DBT and Dask. Experience in Python data science space - LangChain, LangSmith, pandas, numpy, sci kit learn, scipy, hugging face etc. Understanding of statistical and machine learning models. Knowledge of experimental design More ❯