126 to 150 of 302 Apache Airflow Jobs

Strong SQL and Python skills for building and optimising data pipelines Experience working with cloud platforms (e.g., AWS, GCP, or Azure) Familiarity with modern data stack tools (e.g., dbt, Airflow, Snowflake, Redshift, or BigQuery) Understanding of data modelling and warehousing principles Experience working with large datasets and distributed systems What's in it for you? Up to £70k Hybrid More ❯

experience with Cloud infrastructure (ideally AWS), DevOps technologies such as Docker or Terraform and CI/CD processes and tools. Have previously worked with MLOps tools like MLFlow and Airflow, or on common problems such as model and API monitoring, data drift and validation, autoscaling, access permissions Have previously worked with monitoring tools such as New Relic or Grafana … and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github Actions More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for More ❯

engineers Collaborate across engineering, data science, and product teams to deliver business impact Skills & Experience: Expert in SQL , dbt , and cloud data warehouses (e.g., BigQuery, Redshift) Strong experience with Airflow , Python , and multi-cloud environments (AWS/GCP) Proven background in designing and scaling analytics solutions in agile environments Proven experience as an Analytics Engineer Nice to Have: Experience More ❯

oversight across the data platform, including data pipelines, orchestration and modelling. Lead the team in building and maintaining robust data pipelines, data models, and infrastructure using tools such as Airflow, AWS Redshift, DBT and Looker.Ensuring the team follows agile methodologies to improve delivery cadence and responsiveness. Contribute to hands-on coding, particularly in areas requiring architectural input, prototyping, or … mentoring skills and ability to foster team growth and development Strong understanding of the data engineering lifecycle, from ingestion to consumption Hands-on experience with our data stack (Redshift, Airflow, Python, DVT, MongoDB, AWS, Looker, Docker) Understanding of data modelling, transformation, and orchestration best practices Experience delivering both internal analytics platforms and external data-facing products Knowledge of modern More ❯

oversight across the data platform, including data pipelines, orchestration and modelling. Lead the team in building and maintaining robust data pipelines, data models, and infrastructure using tools such as Airflow, AWS Redshift, DBT and Looker.Ensuring the team follows agile methodologies to improve delivery cadence and responsiveness. Contribute to hands-on coding, particularly in areas requiring architectural input, prototyping, or … mentoring skills and ability to foster team growth and development Strong understanding of the data engineering lifecycle, from ingestion to consumption Hands-on experience with our data stack (Redshift, Airflow, Python, DVT, MongoDB, AWS, Looker, Docker) Understanding of data modelling, transformation, and orchestration best practices Experience delivering both internal analytics platforms and external data-facing products Knowledge of modern More ❯

oversight across the data platform, including data pipelines, orchestration and modelling. Lead the team in building and maintaining robust data pipelines, data models, and infrastructure using tools such as Airflow, AWS Redshift, DBT and Looker.Ensuring the team follows agile methodologies to improve delivery cadence and responsiveness. Contribute to hands-on coding, particularly in areas requiring architectural input, prototyping, or … mentoring skills and ability to foster team growth and development Strong understanding of the data engineering lifecycle, from ingestion to consumption Hands-on experience with our data stack (Redshift, Airflow, Python, DVT, MongoDB, AWS, Looker, Docker) Understanding of data modelling, transformation, and orchestration best practices Experience delivering both internal analytics platforms and external data-facing products Knowledge of modern More ❯

trusted, reliable and available . The technology underpinning these capabilities includes industry leading data and analytics products such as Snowflake, Tableau, DBT, Talend, Collibra, Kafka/Confluent , Astronomer/Airflow , and Kubernetes . This forms part of a longer-term strategic direction to implement Data Mesh, and with it establish shared platform s that enables a connected collection of … and driv ing a culture of iterative improvemen t. Modern data stack - hands-on deploy ment and govern ance of enterprise technologies at scale (e.g. Snowflake, Tableau, DBT, Fivetran , Airflow, AWS , GitHub, Terraform, etc ) for self-service workloads . Thought leadership and influencing - deep interest in data platforms landscape to build well-articulated proposals that are supported by strong More ❯

and meeting deadlines. Proficiency in SQL (BigQuery), Python, Git/GitHub, and preferably Looker (Tableau or PowerBI are acceptable as well) Above average knowledge of DBT, Docker, GCP, and Airflow Experience in the cryptocurrency industry, fintech sector, or platform-type businesses is preferred but not required. Personal Attributes Analytical mindset with a passion for data-driven decision-making. Strong … ambitious with a results-oriented attitude and continuous improvement mindset Technologies you will work with Python SQL (BigQuery) GCP EPPO for experimentation DBT, Docker, Cloud Run/Kubernetes, and Airflow for data orchestration and data pipelines Looker data visualization Git and GitHub for code collaboration Ability to leverage AI tools such as Cursor and LLMs in the day-to More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

of engineers, and work closely with cross-functional teams to deliver high-impact data solutions. Key Responsibilities: Architect and maintain robust data pipelines using AWS services (Glue, Lambda, S3, Airflow) Lead the migration and optimisation of data workflows into Snowflake. Collaborate with analysts, data scientists, and product teams to deliver clean, reliable data. Define and enforce best practices in More ❯

data accessibility and quality. Key Skills & Experience Required – About You: Essential: Strong proficiency in Python, SQL, and Jinja Experience with cloud platforms (preferably AWS) Familiarity with orchestration tools (ideally Airflow) Experience building CI/CD workflows (ideally using GitHub Actions) Up-to-date knowledge of modern data engineering practices Proven ability to design and develop scalable data pipelines Strong More ❯

analytics platforms. Experience managing data products or platforms, ideally customer data platforms (CDPs), data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data engineering workflows, data tools (dbt, Airflow), and cloud data platforms (AWS, GCP, Azure). Familiarity with data modelling, data pipelines, ETL/ELT processes, and APIs. Knowledge of GDPR, data ethics, and governance practices. Strong More ❯

analytics platforms. Experience managing data products or platforms, ideally customer data platforms (CDPs), data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data engineering workflows, data tools (dbt, Airflow), and cloud data platforms (AWS, GCP, Azure). Familiarity with data modelling, data pipelines, ETL/ELT processes, and APIs. Knowledge of GDPR, data ethics, and governance practices. Strong More ❯

more. Technical Requirements: Advanced proficiency in Python and modern software engineering practices. Experience architecting solutions using major cloud platforms (Azure, AWS, GCP). Familiarity with technologies such as Databricks, Airflow, dbt, Snowflake, GitHub CI/CD, and infrastructure-as-code. Strong background across at least several of the following areas: Cloud Engineering, Data Platform Architecture, DevOps, MLOps/LLMOps. More ❯

more. Technical Requirements: Advanced proficiency in Python and modern software engineering practices. Experience architecting solutions using major cloud platforms (Azure, AWS, GCP). Familiarity with technologies such as Databricks, Airflow, dbt, Snowflake, GitHub CI/CD, and infrastructure-as-code. Strong background across at least several of the following areas: Cloud Engineering, Data Platform Architecture, DevOps, MLOps/LLMOps. More ❯

more. Technical Requirements: Advanced proficiency in Python and modern software engineering practices. Experience architecting solutions using major cloud platforms (Azure, AWS, GCP). Familiarity with technologies such as Databricks, Airflow, dbt, Snowflake, GitHub CI/CD, and infrastructure-as-code. Strong background across at least several of the following areas: Cloud Engineering, Data Platform Architecture, DevOps, MLOps/LLMOps. More ❯

degree in Computer Science, Engineering, or equivalent practical experience Desirable: Experience with LLMs or transformer-based architectures (e.g., OpenAI, Mistral, or custom-trained models) Familiarity with tools such as Airflow, Spark, or Dask for large-scale data processing Awareness of AI ethics, data privacy, and legal considerations in high-stakes environments People Source Consulting Ltd is acting as an More ❯

questions and assess system efficacy. Ability to communicate complex technical ideas in a clear, non-technical manner. Optional Skills: Familiarity with LLMs Previous experience in Cybersecurity Previous experience with Airflow or similar ML pipeline orchestration tools Experience with large scale ML system and data infrastructure Previous experience in behavioural modeling techniques PhD or equivalent proven experience in ML research More ❯

scikit-learn, Hugging Face). Solid software engineering background: data structures, algorithms, distributed systems, and version control (Git). Knowledge of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect), and streaming frameworks (Spark, Kafka). Strong communication skills-able to explain complex concepts to technical and non-technical stakeholders. Preferred (Nice-to-Have) Experience in early-stage More ❯

pipelines. Implement and optimize automation processes using infrastructure-as-code (Terraform) Build and maintain data pipelines using Airflow. Manage our tech stack including Python, Node.js, PostgreSQL, MongoDB, Kafka, and Apache Iceberg. Optimize infrastructure costs and develop strategies for efficient resource utilization. Provide critical support by monitoring services and resolving production issues. Contribute to the development of new services as More ❯

pipelines. Implement and optimize automation processes using infrastructure-as-code (Terraform) Build and maintain data pipelines using Airflow. Manage our tech stack including Python, Node.js, PostgreSQL, MongoDB, Kafka, and Apache Iceberg. Optimize infrastructure costs and develop strategies for efficient resource utilization. Provide critical support by monitoring services and resolving production issues. Contribute to the development of new services as More ❯