robust way possible! Diverse training opportunities and social benefits (e.g. UK pension schema) What do you offer? Strong hands-on experience working with modern Big Data technologies such as Apache Spark, Trino, Apache Kafka, Apache Hadoop, Apache HBase, Apache Nifi, ApacheAirflow, Opensearch Proficiency in cloud-native technologies such as containerization and Kubernetes More ❯
privacy, and security, ensuring our AI systems are developed and used responsibly and ethically. Tooling the Future: Get hands-on with cutting-edge technologies like Hugging Face, PyTorch, TensorFlow, Apache Spark, ApacheAirflow, and other modern data and ML frameworks. Collaborate and Lead: Partner closely with ML Engineers, Data Scientists, and Researchers to understand their data needs … their data, compute, and storage services. Programming Prowess: Strong programming skills in Python and SQL are essential. Big Data Ecosystem Expertise: Hands-on experience with big data technologies like Apache Spark, Kafka, and data orchestration tools such as ApacheAirflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering More ❯
and evaluation through continuous monitoring and scaling. Build & Optimise AI models in Python: fine-tune state-of-the-art architectures on our in-house GPU cluster. Orchestrate Workflows with ApacheAirflow: schedule, monitor, and maintain complex data and model pipelines. Engineer Cloud Services on AWS (Lambda, ECS/EKS, S3, Redshift, etc.) and automate deployments using GitHub Actions … testing, and monitoring. Startup mindset: proactive, resourceful, ambitious, driven to innovate, eager to learn, and comfortable wearing multiple hats in a fast-moving environment. Desirable: hands-on experience with ApacheAirflow, AWS services (especially Redshift, S3, ECS/EKS), and IaC tools like Pulumi. Why Permutable AI? Hybrid Flexibility: Spend 2+ days/week in our Vauxhall hub. More ❯
Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 700 of the world's leading enterprises, Astronomer … our product's evolution through client feedback. This role is ideal for someone who wants to make a visible impact while growing into an expert in workflow orchestration and Apache Airflow. This is a hybrid role requiring a minimum of 3 days per week onsite, and includes up to 40% travel for business and customer needs. What you get … production. Be a Trusted Advisor: Conduct demos and provide technical guidance to engineering teams, showing them how our platform can transform their workflows. Drive Community Impact: Contribute to the ApacheAirflow community by creating technical content and best practices, positioning Astronomer as a thought leader in workflow orchestration. Influence Product Direction: Act as a liaison by gathering field More ❯
doing? Evolve the Data Platform by designing and building the next generation of the stack. Develop, run and support our batch and real-time data pipelines using tools like Airflow, PlanetScale, Kinesis, Snowflake, Tableau, all in AWS. Collaborate with product managers, data engineers, analysts and data scientists to develop tooling and infrastructure to support their needs. Develop automation and … quality issues. Recent projects the team has delivered: Refactoring of our MySQL Ingestion pipeline for reduced latency and 10x scalability. Redshift -> Snowflake migration Unified Local Analytics Development Environment for Airflow and DBT Building our next generation company metrics framework, adding anomaly detection and alerting, and enabling easier discovery and consumption. About you You have 5+ years of full-time … might be more valuable than your direct technical contributions on a project. You care about your craft In addition it would be a bonus if you have Worked with ApacheAirflow - we use Airflow extensively to orchestrate and schedule all of our data workflows. A good understanding of the quirks of operating Airflow at scale would More ❯
Experience in using modern data architectures, such as lakehouse. Experience with CI/CD pipelines and version control systems like Git. Knowledge of ETL tools and technologies such as ApacheAirflow, Informatica, or Talend. Knowledge of data governance and best practices in data management. Familiarity with cloud platforms and services such as AWS, Azure, or GCP for deploying … and managing data solutions. Strong problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues. SQL (for database management and querying) Apache Spark (for distributed data processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP More ❯
data architectures, such as lakehouse. Experience with CI/CD pipelines, version control systems like Git, and containerization (e.g., Docker). Experience with ETL tools and technologies such as ApacheAirflow, Informatica, or Talend. Strong understanding of data governance and best practices in data management. Experience with cloud platforms and services such as AWS, Azure, or GCP for … deploying and managing data solutions. Strong problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues. SQL (for database management and querying) Apache Spark (for distributed data processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or More ❯
or other testing methodologies Preferred: Familiarity with PostgreSQL and Snowflake Preferred: Familiarity with Web Frameworks such as Django, Flask or FastAPI Preferred: Familiarity with event streaming platforms such as Apache Kafka Preferred: Familiarity with data pipeline platforms such as ApacheAirflow Preferred: Familiarity with Java Preferred: Experience in one or more relevant financial areas (market data, order More ❯
. Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Knowledge of containerization and orchestration tools (e.g., Docker, ECS, Kubernetes). Familiarity of data orchestration tools (e.g. Prefect, ApacheAirflow). Familiarity with CI/CD pipelines and DevOps practices. Familiarity with Infrastructure-as-code tools (e.g. Terraform, AWS CDK). Employee Benefits: At Intelmatix, our benefits More ❯
delivering end-to-end AI/ML projects. Nice to Have: Exposure to LLMs (Large Language Models), generative AI , or transformer architectures . Experience with data engineering tools (Spark, Airflow, Snowflake). Prior experience in fintech, healthtech, or similar domains is a plus. More ❯
business glossary, and data mapping framework using metadata management and data catalog tools. Automate data classification, lineage tracking, and policy enforcement through scripts, APIs, and orchestration tools (e.g., dbt, Airflow). Map & Visualize Data Flows : Design and maintain clear documentation and visualizations of data movement across systems, focusing on sensitive and business-critical data. Drive Cross-Functional Alignment: Collaborate … governance SME; support teams with tooling, guidance, and best practices. About You: Strong technical foundation in data governance architecture and tooling. You've worked with tools such as DataHub, ApacheAirflow, AWS, dbt, Snowflake, BigQuery , or similar. Hands-on experience building and maintaining centralized data inventories, business glossaries, and data mapping frameworks. Proficient in automating data classification and … lineage using scripting languages like Python , SQL , or Java , along with orchestration tools such as Airflow and dbt . 5+ years of experience in data governance, privacy, or data engineering roles-especially in settings that integrate governance tightly into data platform design. Familiarity with privacy-by-design , data minimization , and regulatory standards including GDPR, ISO 27001, SOC 2, and More ❯
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 ❯
building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and More ❯
building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and More ❯
Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB. They are also proficient in Azure Event Hub and Streaming Analytics, Managed Streaming for Apache Kafka, Azure DataBricks with Spark, and other open source technologies like ApacheAirflow and dbt, Spark/Python, or Spark/Scala. Required technical and professional expertise 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 . ApacheAirflow 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 ❯
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 at least one programming language such as Python, Java, or Scala. Strong analytical and problem-solving skills with the ability to work independently and in a 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 ❯
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 ApacheAirflow (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 ❯
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 ApacheAirflow, 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 ❯
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., ApacheAirflow). 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 ❯
