201 to 225 of 432 Remote Apache Airflow Jobs

data quality across the board. Requirements: 5+ years professional experience within Data engineering Strong hands-on experience with Snowflake (required). Familiarity with DBT, Airflow, and AWS (preferred). Background in building and maintaining robust data architectures. Ability to identify and resolve complex data issues and improve data validation More ❯

algorithms Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) Experience with MLOps tools is a plus (e.g., MLflow, DVC, Airflow) Ability to work independently and manage time effectively in a hybrid work setting Fluent in English; French or Dutch is a plus Nice to More ❯

using tools like Segment, PostHog, and GA4. What you need to bring: 4+ years of experience with Python and SQL Experience with DBT and Airflow Vast experience with AWS stack Comfortable engaging with non-technical stakeholders to understand their needs and design appropriate solutions. Nice to haves: Experience integrating More ❯

and CI/CD pipelines. Excellent communication skills and a passion for mentoring and team leadership. Nice to Have Experience with data engineering tools (Airflow, Kafka, Spark). Knowledge of MLOps practices and tools (MLflow, Kubeflow). Contributions to open-source projects or AI research. Why Join? Work on More ❯

best practices Expertise in large-scale data processing and pipeline optimisation Proficient in Python, SQL, and cloud platforms (AWS or similar) Hands-on with Airflow, Fivetran, Snowflake, Docker (or equivalents) Experience with real-time and batch data pipelines Ready for your next move? Apply now or send your CV More ❯

Engineering position. Self-starter, who has experience with building data pipelines in the cloud. Excellent knowledge of PySpark, Python and SQL fundamentals. Familiar with Airflow, Databricks & BigQuery. Exposure with Palantir Foundry would be a huge plus but not essential. Ability to work on messy, complex real-world data challenges. More ❯

data platform (PaaS) Ensure scalable storage solutions (data lakes, data warehouses) to handle structured and unstructured data. Implement ETL/ELT pipelines using Dagster, Airflow, or similar tools. Optimize performance and scalability for large data volumes. Govern data security, compliance, and access controls. Development & DevOps: Strong programming and scripting More ❯

and machine learning concepts Experience with some machine learning/data engineering machine learning tech in Python (such as numpy, pytorch, pandas/polars, airflow, etc) Experience developing data products using large language model, prompt engineering, model evaluation. Experience with web services and programming (such as Python, docker, databases More ❯

data platform (PaaS) Ensure scalable storage solutions (data lakes, data warehouses) to handle structured and unstructured data. Implement ETL/ELT pipelines using Dagster, Airflow, or similar tools. Optimize performance and scalability for large data volumes. Govern data security, compliance, and access controls. Development & DevOps: Strong programming and scripting More ❯

related finance-related degree. Experience with equity or fixed income derivatives volatility models for risk and trading systems. Experience with data engineering frameworks like Airflow, Luigi or Dagster. Experience developing financial model libraries in Python, Java, or C++ Experience with risk and optimization tools such as Aladdin, RiskMetrics, Barra More ❯

a commercial setting Degree in Computer Science or a related field, or equivalent professional experience Solid Python skills, familiarity with data-pipeline frameworks (e.g., Airflow, dbt or similar) and proficient querying SQL databases (we use PostgreSQL and BigQuery) Strong ownership; someone who thrives on taking full responsibility for their More ❯

/or financial instruments including equities, futures, and options Strong Unix skills along with programming skills in Python and experience in Scheduling tools like Airflow Good understanding of networking and system concepts Experience with SQL and the use of databases is a plus The ability to manage multiple tasks More ❯

An understanding (doesn’t need to be experience of) of Cloud Technologies. Development of data pipeline based on SQL with orchestration tools such as Airflow or Tivoli scheduler. Intermediate programming skills around Python. Awareness of CI/CD practices. We’re looking for confident communicators who can break down More ❯

operational businesses Experience using LLMs or AI tools to structure and extract meaning from unstructured data Experience automating workflows and deploying model pipelines (e.g. Airflow, dbt, MLFlow, or similar) Exposure to business planning, pricing, or commercial decision-making Familiarity with geospatial data Experience in fast-scaling startups or operational More ❯

product managers. Nice-to-Haves: Experience with streaming platforms and understanding stream/table transformations. Familiarity with ML system deployment and management (Kubeflow, MLflow, Airflow, Flyte, etc.). Knowledge of monitoring, alerting, and operational best practices for data-intensive systems. Experience with Feature Stores or similar ML data management More ❯

Technologies That Our Data Scientists Use (we Don’t Expect You To Have Experience With All Of These) Python and Databricks Spark, MLFlow, and Airflow for ML Workflows Google Cloud Platform for our analytics infrastructure dbt and BigQuery for data modelling and warehousing Some examples of our data science More ❯

engineering and large language models (LLM) is a plus Proficiency in multiple programming languages Understanding of containerization technologies like Docker and orchestration tools like Airflow We've got your back... We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes More ❯

React frontends. You'll utilise tools such as Terraform for infrastructure-as-code ( IaC ), AWS (Lambda, EC2, EKS, Step Functions, VPC etc.) for ETL, Airflow pipelines, Snowflake, and ensure architectural alignment with AI/ML initiatives and data-driven services. You will serve as the go-to engineer for More ❯

and the ability to align data science work with broader business priorities Nice to Have: Experience with data science tooling (e.g., workflow orchestrators like Airflow, feature stores) Familiarity with visual analytics tools (e.g., Tableau or similar platforms) Experience in gaming, digital commerce, or subscription services A personal interest in More ❯

stack: Frontend Technologies - React, Material UI Backend & Application Frameworks - Go, Node, RabbitMQ Databases - Postgres, MariaDB, MongoDB, ClickHouse, Redis, JupyterLab, Metabase Data Engineering & Orchestration - Python, Airflow, Kafka, DataHub Cloud & Infrastructure - AWS, K8s DevOps & CI/CD - Git, GitLab CI, DBS, Grafana, ELK, Prometheus, Docker, Docker Compose Why join us? Shape More ❯

Technologies That Our Data Scientists Use (we Don't Expect You To Have Experience With All Of These) Python and Databricks Spark, MLFlow, and Airflow for ML Workflows Google Cloud Platform for our analytics infrastructure dbt and BigQuery for data modelling and warehousing Some examples of our data science More ❯

in data pipelines across cloud/on-premises, using Azure and other technologies. Experienced in orchestrating data workflows and Kubernetes clusters on AKS using Airflow, Kubeflow, Argo, Dagster or similar. Skilled with data ingestion tools like Airbyte, Fivetran, etc. for diverse data sources. Expert in large-scale data processing More ❯

by collaborating with product squads and business stakeholders Develop robust, production-quality software artifacts using Python and large-scale data workflow orchestration platforms (e.g., Airflow), while managing team resources & timelines Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure Champion ML governance, ensuring More ❯

understanding of CRM and Customer Success data models (Salesforce, HubSpot, Gainsight). Strong experience building and maintaining data pipelines with modern tools (e.g., dbt, Airflow, Fivetran, Snowflake). Proven success developing and operationalizing predictive models using Python or SQL. Expert-level skills in data visualization and BI platforms (e.g. More ❯

and the ability to align data science work with broader business priorities Nice to Have: Experience with data science tooling (e.g., workflow orchestrators like Airflow, feature stores) Familiarity with visual analytics tools (e.g., Tableau or similar platforms) Experience in gaming, digital commerce, or subscription services A personal interest in More ❯