326 to 350 of 482 Remote Apache Airflow Jobs

datasets, cross-validation, performance visualisation, and use hosted APIs; explore techniques like time-series forecasting, clustering, or Bayesian inference. Orchestration and Parallelisation : Manage workflows with tools like Metaflow, MLFlow, AirFlow, or DVC; utilise parallelisation frameworks like PySpark or Ray for efficient model processing. Exposure to cloud platforms (AWS, Azure, GCP) Why you should join us Artefact is revolutionizing marketing More ❯

development of a new global 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 skills in Python. Knowledge of More ❯

Solid understanding of data science 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 etc.) Great to (but not More ❯

development of a new global 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 skills in Python. Knowledge of More ❯

to have: Financial engineering or 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, Axioma - as a model developer More ❯

or python developer, ideally in 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 work. Curious mindset; thrives on More ❯

understanding of electronic trading and/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 in a fast-paced environment More ❯

scalable solutions. Excellent proficiency in SQL and working with data warehousing technologies , such as Snowflake, Databricks and/or dbt Knowledge of orchestration and version control tools , such as Airflow and Git hub In-d epth knowledge of data visualisation tools , such as Looker or Tableau Collaborative working style with desire to share knowledge that enables the entire team More ❯

and/or Data Warehousing. 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 technical concepts in a clear More ❯

logistics, marketplaces, or similarly complex 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 teams We're flexible on More ❯

data scientists, software engineers, and 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 tools. What We Offer: Competitive More ❯

Data Science. These Are Some 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 work can be found in More ❯

.NET framework backend services and 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: End-to-end data migration More ❯

of partners A collaborative attitude 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 gaming and the entertainment industry More ❯

data engineering Our current tech 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 the future of a data More ❯

Data Science. These Are Some 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 work can be found in More ❯

ML solutions into existing workflows 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 adherence to guidelines, monitoring SLAs More ❯

revenue reporting and reconciliation. Deep 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., Looker, Tableau, Metabase). Excellent More ❯

of partners A collaborative attitude 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 gaming and the entertainment industry More ❯

Participate in the on-call rotation (about 1 week per quarter) to support our production services. Our stack is best summed up by: Databricks, AWS(S3), Python/Typescript, Airflow, dbt, Kafka, Braintrust. Senior Machine Learning Engineer vs Other Roles At Zapier How do we discern between a ML Engineer vs Applied AI Engineer? The following are discrete topics More ❯

revenue reporting and reconciliation. Deep 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., Looker, Tableau, Metabase). Excellent More ❯

In 2025 our ambition is to be a high-performing, delivery-focused organisation and the best engineering organisation for those who value meaningful career growth. We are looking for a UK-based Engineering Manager to run one of Depop's More ❯

If you need support in completing the application or if you require a different format of this document, please get in touch with at UKI.recruitment@tcs.com or call TCS London Office number 02031552100/+44 204 520 2575 with the More ❯

If you need support in completing the application or if you require a different format of this document, please get in touch with at UKI.recruitment@tcs.com or call TCS London Office number 02031552100/+44 204 520 2575 with the More ❯

If you need support in completing the application or if you require a different format of this document, please get in touch with at UKI.recruitment@tcs.com or call TCS London Office number 02031552100/+44 204 520 2575 with the More ❯