14 of 14 Remote Permanent Dagster Jobs

aggressive timelines · Comfortable working autonomously with minimal supervision · Excellent communication skills with non-technical stakeholders Desirable Experience · Financial services or wealth management background · Tableau or BI tool integration · dbt, Dagster, or modern data stack tools Our Tech Stack · Frontend: React, TypeScript, Modern CSS · Backend: Python (FastAPI/Flask), Node.js · Data: Apache Iceberg, dbt, Tableau · Infrastructure: AWS EKS, Docker, Terraform More ❯

especially model training and experimentation Proficiency in programming languages such as Python, Scala, or Java Cloud experience (AWS, GCP, or Azure), plus modern data technologies (e.g. Spark, Kafka, Airflow, Dagster, Kedro) Background in industries with complex datasets, such as healthtech, NLP, or other large-scale data applications Leadership opportunity Alongside core engineering hires, the team is also seeking one More ❯

especially model training and experimentation Proficiency in programming languages such as Python, Scala, or Java Cloud experience (AWS, GCP, or Azure), plus modern data technologies (e.g. Spark, Kafka, Airflow, Dagster, Kedro) Background in industries with complex datasets, such as healthtech, NLP, or other large-scale data applications Leadership opportunity Alongside core engineering hires, the team is also seeking one More ❯

practices across engineering teams. Passion for hands-on engineering—comfortable both whiteboarding architecture and prototyping in code. Deep, hands-on expertise with modern data stack technologies including AWS, Snowflake, Dagster, dbt, and Spark. Excellent collaboration and communication skills; able to engage both technical and non-technical audiences. Preferred: Understanding of the asset management business and/or financial markets. More ❯

modern, cloud-first environment with real autonomy — designing and building data pipelines, improving infrastructure, and driving innovation across the data platform. Tech Stack: 🔹 Snowflake 🔹 Python (FastAPI, Pydantic) 🔹 Airflow/Dagster 🔹 AWS + Terraform 🔹 CI/CD (GitHub Actions) (Bonus: Kafka, dbt/SQLMesh, data quality & governance tools) What’s on Offer: 💰 Up to £110,000 + annual bonus + More ❯

Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift More ❯

Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift More ❯

Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift More ❯

Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift More ❯

Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift More ❯

recovery processes. Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency More ❯

recovery processes. Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency More ❯

recovery processes. Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency More ❯

and the business. Primary Responsibilities Design and implement the core data stack end-to-end, working across ingestion, processing, and delivery systems (S3/Athena, Neon Postgres, Tinybird, Modal, Dagster). Define the strategy for integrating AI/ML models and LLMs into data workflows for automated enrichment and agentic features. Develop entity-matching algorithms (potentially using ML) to … data stacks and cloud technologies (AWS, Azure, or GCP). Expert knowledge of Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... … and scale a data function over time. Take ownership, empower others, and drive meaningful change Tech Stack: Cloud & storage: S3, Athena, Glue Databases: Neon Postrgres, Tinybird Compute & Orchestration: Modal, Dagster Languages: Python, SQL AI/ML: LLMs, agentic workflows Benefits Currently Offered: £130K–£150K base salary + meaningful equity as a founding employee. Private medical insurance Life assurance Gym More ❯