26 to 50 of 267 Apache Airflow Jobs in the UK

systems, with a focus on data quality and reliability. Design and manage data storage solutions, including databases, warehouses, and lakes. Leverage cloud-native services and distributed processing tools (e.g., Apache Flink, AWS Batch) to support large-scale data workloads. Operations & Tooling Monitor, troubleshoot, and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and … ELT pipelines and data architectures. Hands-on expertise with cloud platforms (e.g., AWS) and cloud-native data services. Comfortable with big data tools and distributed processing frameworks such as Apache Flink or AWS Batch. Strong understanding of data governance, security, and best practices for data quality. Effective communicator with the ability to work across technical and non-technical teams. … Additional Strengths Experience with orchestration tools like Apache Airflow. Knowledge of real-time data processing and event-driven architectures. Familiarity with observability tools and anomaly detection for production systems. Exposure to data visualization platforms such as Tableau or Looker. Relevant cloud or data engineering certifications. What we offer: A collaborative and transparent company culture founded on Integrity, Innovation and More ❯

meetings. What You Need to Succeed Strong skills in Python and SQL Demonstrable hands-on experience in AWS cloud Data ingestions both batch and streaming data and data transformations (Airflow, Glue, Lambda, Snowflake Data Loader, FiveTran, Spark, Hive etc.). Apply agile thinking to your work. Delivering in iterations that incrementally build on what went before. Excellent problem-solving … translate concepts into easily understood diagrams and visuals for both technical and non-technical people alike. AWS cloud products (Lambda functions, Redshift, S3, AmazonMQ, Kinesis, EMR, RDS (Postgres . Apache Airflow for orchestration. DBT for data transformations. Machine Learning for product insights and recommendations. Experience with microservices using technologies like Docker for local development. Apply engineering best practices More ❯

collaboratively Proficiency in multiple programming languages Technologies: Scala, Java, Python, Spark, Linux, shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) Experience with process scheduling platforms like Apache Airflow Open to working with proprietary GS technologies such as Slang/SECDB Understanding of compute resources and performance metrics Knowledge of distributed computing, including parallel and cloud More ❯

Strong knowledge of algorithms, design patterns, OOP, threading, multiprocessing, etc. Experience with SQL, NoSQL, or tick databases Experience working in a Unix environment and git Familiarity with Kafka, Docker, AirFlow, Luigi Strong communication skills in verbal and written English. Domain knowledge in futures & swaps is a plus Highly competitive compensation and bonus structure Meritocratic environment with ample opportunity for More ❯

MySQL, PostgreSQL, or Oracle. Experience with big data technologies such as Hadoop, Spark, or Hive. Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow. Proficiency in Python and at least one other programming language such as Java, or Scala. Willingness to mentor more junior members of the team. Strong analytical and problem More ❯

with multiple languages • Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant) • Experience in working with process scheduling platforms like Apache Airflow. • Should be ready to work in GS proprietary technology like Slang/SECDB • An understanding of compute resources and the ability to interpret performance metrics (e.g., CPU, memory More ❯

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

Cloud Data Warehouse - Snowflake AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda Data Governance & Quality - Collate & Monte Carlo Infrastructure as Code - Terraform Data Integration & Transformation - Python, DBT, Fivetran, Airflow CI/CD - Github Actions/Jenkins Nice to Have Experience Understanding of various data architecture paradigms (e.g., Data Lakehouse, Data Warehouse, Data Mesh) and their applicability to different More ❯

Cloud Data Warehouse - Snowflake AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda Data Governance & Quality - Collate & Monte Carlo Infrastructure as Code - Terraform Data Integration & Transformation - Python, DBT, Fivetran, Airflow CI/CD - Github Actions/Jenkins Business Intelligence - Looker Skills & Attributes We'd Like To See: Extensive experience in data engineering, including designing and maintaining robust data pipelines. More ❯

analysis, and supporting complex client agreements. This is a hands-on engineering role working closely with stakeholders and system owners. You'll be expected to code daily (Python), manage Airflow pipelines (MWAA), build ETL processes from scratch, and improve existing workflows for better performance and scalability. Key responsibilities Design and build robust ETL pipelines using Python and AWS services … Own and maintain Airflow workflows Ensure high data quality through rigorous testing and validation Analyse and understand complex data sets before pipeline design Collaborate with stakeholders to translate business requirements into data solutions Monitor and improve pipeline performance and reliability Maintain documentation of systems, workflows, and configs Tech environment Python, SQL/PLSQL (MS SQL + Oracle), PySpark Apache Airflow (MWAA), AWS Glue, Athena AWS services (CDK, S3, data lake architectures) Git, JIRA You should apply if you have: Strong Python and SQL skills Proven experience designing data pipelines in cloud environments Hands-on experience with Airflow (ideally MWAA) Background working with large, complex datasets Experience in finance or similar high-volume, regulated industries (preferred but More ❯

Troubleshooting: Oversee pipeline performance, address issues promptly, and maintain comprehensive data documentation. What Youll Bring Technical Expertise: Proficiency in Python and SQL; experience with data processing frameworks such as Airflow, Spark, or TensorFlow. Data Engineering Fundamentals: Strong understanding of data architecture, data modelling, and scalable data solutions. Backend Development: Willingness to develop proficiency in backend technologies (e.g., Python with … Django) to support data pipeline integrations. Cloud Platforms: Familiarity with AWS or Azure, including services like Apache Airflow, Terraform, or SageMaker. Data Quality Management: Experience with data versioning and quality assurance practices. Automation and CI/CD: Knowledge of build and deployment automation processes. Experience within MLOps A 1st class Data degree from one of the UKs top More ❯

TransferGo. 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 … methodologies. Collaborating with stakeholders to define data strategies, implement data governance policies, and ensure data security and compliance. About you: Strong technical proficiency in data engineering technologies, such as Apache Airflow, ClickHouse, ETL tools, and SQL databases. Deep understanding of data modeling, ETL processes, data integration, and data warehousing concepts. Proficiency in programming languages commonly used in data More ❯

Maintenance - Implement robust logging, alerting, and performance monitoring for integrations. Continuous Improvement - Champion enhancements to integration architectures and best practices. Skills & Experience Required Experience with workflow orchestration tools (e.g., Apache Airflow). Proven track record in backend development (e.g., Node.js, Python, Java). Strong knowledge of API design, integration methods (REST, Webhooks, GraphQL), and authentication protocols (OAuth2, JWT More ❯

Maintenance - Implement robust logging, alerting, and performance monitoring for integrations. Continuous Improvement - Champion enhancements to integration architectures and best practices. Skills & Experience Required Experience with workflow orchestration tools (e.g., Apache Airflow). Proven track record in backend development (e.g., Node.js, Python, Java). Strong knowledge of API design, integration methods (REST, Webhooks, GraphQL), and authentication protocols (OAuth2, JWT More ❯

of real-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 More ❯

Computer Science, Engineering, or a related field, or equivalent industry experience. Preferred Qualifications Experience or interest in mentoring junior engineers. Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow). Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, or data.table/R. Experience working with AWS or other cloud platforms. Knowledge More ❯

developing and implementing enterprise data models. Experience with Interface/API data modelling. Experience with CI/CD GITHUB Actions (or similar) Knowledge of Snowflake/SQL Knowledge of Apache Airflow Knowledge of DBT Familiarity with Atlan for data catalog and metadata management Understanding of iceberg tables Who we are: Were a business with a global reach that More ❯

REST APIs and integration techniques Familiarity with data visualization tools and libraries (e.g. Power BI) Background in database administration or performance tuning Familiarity with data orchestration tools, such as Apache Airflow Previous exposure to big data technologies (e.g. Hadoop, Spark) for large data processing Strong analytical skills, including a thorough understanding of how to interpret customer business requirements More ❯

of Science Degree in software engineering or a related field Proficiency in English spoken and written Nice-to-Haves: Experience with ETL/ELT pipeline design and tools (e.g., Apache Airflow). Familiarity with Change Data Capture (CDC) solutions. Knowledge of database services on other cloud platforms (e.g., Azure SQL Database, Google Cloud Spanner). Understanding of ORM More ❯

of Science Degree in software engineering or a related field Proficiency in English spoken and written Nice-to-Haves: Experience with ETL/ELT pipeline design and tools (e.g., Apache Airflow). Familiarity with Change Data Capture (CDC) solutions. Knowledge of database services on other cloud platforms (e.g., Azure SQL Database, Google Cloud Spanner). Understanding of ORM More ❯

team. 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 More ❯

/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 document scalable, reliable data models Comfortable gathering business requirements and translating them into data architecture Strong problem More ❯

team. 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 More ❯

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 ❯

retrieval and pipeline development Experience with IaC tools such as Terraform or Ansible for deployment and infrastructure management Hands-on experience with; ETL/ELT orchestration and pipeline tools (Airflow, Airbyte, DBT, etc.) Data warehousing tools and platforms (Snowflake, Iceberg, etc.) SQL databases, particularly MySQL Desired Experience: Experience with cloud-based services, particularly AWS Proven ability to manage stakeholders More ❯