1 to 25 of 112 Apache Jobs

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, Apache Airflow, Opensearch Proficiency in cloud-native technologies such as containerization and Kubernetes Strong More ❯

production issues. Optimize applications for performance and responsiveness. Stay Up to Date with Technology: Keep yourself and the team updated on the latest Python technologies, frameworks, and tools like Apache Spark, Databricks, Apache Pulsar, Apache Airflow, Temporal, and Apache Flink, sharing knowledge and suggesting improvements. Documentation: Contribute to clear and concise documentation for software, processes, and … Experience with cloud platforms like AWS, GCP, or Azure. DevOps Tools: Familiarity with containerization (Docker) and infrastructure automation tools like Terraform or Ansible. Real-time Data Streaming: Experience with Apache Pulsar or similar systems for real-time messaging and stream processing is a plus. Data Engineering: Experience with Apache Spark, Databricks, or similar big data platforms for processing … large datasets, building data pipelines, and machine learning workflows. Workflow Orchestration: Familiarity with tools like Apache Airflow or Temporal for managing workflows and scheduling jobs in distributed systems. Stream Processing: Experience with Apache Flink or other stream processing frameworks is a plus. Desired Skills Asynchronous Programming: Familiarity with asynchronous programming tools like Celery or asyncio. Frontend Knowledge: Exposure More ❯

environments. Strong understanding of system design, scalability, and clean coding practices. Familiarity with application monitoring solutions Data Engineering 5+ years building scalable and reliable data pipelines using Databricks and Apache Spark. We need both. Experience with cloud data warehouse/data lake architectures and tooling. Experience building solutions using cloud providers, preferably Azure (AWS/GCP also valued). More ❯

customer data Continuously improve existing systems, introducing new technologies and methodologies that enhance efficiency, scalability, and cost optimisation Essential Skills for the Senior Data Engineer: Proficient with Databricks and Apache Spark, including performance tuning and advanced concepts such as Delta Lake and streaming Strong programming skills in Python with experience in software engineering principles, version control, unit testing and More ❯

. AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT design and data orchestration, specifically with Apache Airflow. SQL Mastery: Strong SQL skills with significant experience in query tuning and performance optimisation. Programming Proficiency: Proficiency in Python and Bash (for data processing, scripting, and automation). More ❯

. AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT design and data orchestration, specifically with Apache Airflow. SQL Mastery: Strong SQL skills with significant experience in query tuning and performance optimisation. Programming Proficiency: Proficiency in Python and Bash (for data processing, scripting, and automation). More ❯

Azure, or GCP, with hands-on experience in cloud-based data services. Proficiency in SQL and Python for data manipulation and transformation. Experience with modern data engineering tools, including Apache Spark, Kafka, and Airflow. Strong understanding of data modelling, schema design, and data warehousing concepts. Familiarity with data governance, privacy, and compliance frameworks (e.g., GDPR, ISO27001). Hands-on More ❯

skills We're excited if you have 7+ years of experience delivering multi tier, highly scalable, distributed web applications Experience working with Distributed computing frameworks knowledge: Hive/Hadoop, Apache Spark, Kafka, Airflow Working with programming languages Python , Java, SQL. Working on building ETL (Extraction Transformation and Loading) solution using PySpark Experience in SQL/NoSQL database design Deep More ❯

the delivery of robust, cloud-native solutions that support analytics, automation, and digital transformation. Data Engineering, Full Stack & Platform Development Design and implement scalable data pipelines using tools like Apache Spark, Airflow, or dbt.Build and maintain data lakes, warehouses, and real-time streaming solutions. Develop APIs and microservices to expose data securely and efficiently. Ensure data quality, governance, and More ❯

and Disaster Recovery Planning Data Engineering concepts and frameworks such as batch processing, stream processing, replication, SQL, DBT, Talend, Informatica, Python, Snowpark, PySpark, DataFrames, storage formats (e.g. Parquet, Avro, Apache Iceberg, Delta Lake), Orchestration and DevOps Business Intelligence and analytics solutions such as Tableau, Power BI, MicroStrategy, Thoughtspot, SAS, Streamlit, and techniques such as time series analysis, Advanced SQL More ❯

AWS (S3, Lambda, Glue, Redshift) and/or Azure (Data Lake, Synapse). Programming & Scripting:Proficiency in Python, SQL, PySpark etc. ETL/ELT & Streaming:Expertise in technologies like Apache Airflow, Glue, Kafka, Informatica, EventBridge etc. Industrial Data Integration:Familiarity with OT data schema originating from OSIsoft PI, SCADA, MES, and Historian systems. Information Modeling:Experience in defining semantic More ❯

understanding of data modelling, warehousing, and performance optimisation. Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with big data frameworks (e.g. Apache Spark, Hadoop). Strong knowledge of data governance, security, and compliance. Ability to lead technical projects and mentor junior engineers. Excellent problem-solving skills and experience in agile environments. More ❯

understanding of data modelling, warehousing, and performance optimisation. Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with big data frameworks (e.g. Apache Spark, Hadoop). Strong knowledge of data governance, security, and compliance. Ability to lead technical projects and mentor junior engineers. Excellent problem-solving skills and experience in agile environments. More ❯

and Responsibilities While in this position your duties may include but are not limited to: Support the design, development, and maintenance of scalable data pipelines using tools such as Apache Airflow, dbt, or Azure Data Factory. Learn how to ingest, transform, and load data from a variety of sources, including APIs, databases, and flat files. Assist in the setup More ❯

London occasionally. About you : You have strong Python backend software engineer skills You have experience working with large data sets You have experience of using PySpark and ideally also Apache Spark You believe in automating wherever possible You're a collaborative problem solver with great communication skills Other technology in the stack includes: FastAPI, Django, Airflow, Kafka, ETL, CI More ❯

Google Cloud, Databricks) are a strong plus Technical Skills: • Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL) • Familiarity with data pipeline and workflow management tools (e.g., Apache Airflow) • Experience with programming languages such as Python, Java, or Scala. Python is highly preferred • Basic understanding of cloud platforms and services (e.g., AWS, Azure, Google Cloud) • Knowledge of More ❯

Azure Storage, Medallion Architecture, and working with data formats such as JSON, CSV, and Parquet. • Strong understanding of IT concepts, including security, IAM, Key Vault, and networking. • Exposure to Apache Airflow and DBT is a bonus. • Familiarity with agile principles and practices. • Experience with Azure DevOps pipelines. The "Nice to Haves": • Certification in Azure or related technologies. • Experience with More ❯

at least one cloud data platform (e.g. AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). · Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow etc · Good knowledge of stream and batch processing solutions like Apache Flink, Apache Kafka/· Good knowledge of log management, monitoring, and analytics More ❯

Google Cloud Platform (GCP) - especially BigQuery, Cloud Storage, Dataproc, Pub/Sub, and Composer (Airflow). Expertise in Python and SQL for ETL, data transformation, and orchestration. Experience with Apache Airflow DAG development and scheduling best practices. Strong understanding of data warehouse and data lake concepts. Knowledge of Spark or PySpark for big data processing. Familiarity with CI/ More ❯

frameworks Confident using Git and working within Agile/SCRUM teams Experience mentoring junior developers Knowledge of Oracle/relational databases, MongoDB, and GitLab CI/CD Familiarity with Apache NiFi, JavaScript/TypeScript, and React Experience with Elasticsearch, Kibana, Hibernate, and the Atlassian suite (Bitbucket, Jira, Confluence) Desirable; Experience with JSF (PrimeFaces) Knowledge of AWS and cloud-ready More ❯

SQL scripting. Proficiency in AWS services such as S3, Lambda, Glue, Redshift, and CloudWatch. Strong programming skills in Python or Scala for data processing. Experience with orchestration tools like Apache Airflow or AWS Step Functions. Familiarity with version control systems (e.g., Git) and CI/CD pipelines. Excellent problem-solving and communication skills. Preferred Qualifications: Snowflake certification. Experience with More ❯

of Kubernetes, Docker, and cloud-native data ecosystems. Demonstrable experience with Infrastructure as Code tools (Terraform, Ansible). Hands-on experience with PostgreSQL and familiarity with lakehouse technologies (e.g. Apache Parquet, Delta Tables). Exposure to Spark, Databricks, and data lake/lakehouse environments. Understanding of Agile development methods, CI/CD pipelines, GitHub, and automated testing. Practical experience More ❯

of Kubernetes, Docker, and cloud-native data ecosystems. Demonstrable experience with Infrastructure as Code tools (Terraform, Ansible). Hands-on experience with PostgreSQL and familiarity with lakehouse technologies (e.g. Apache Parquet, Delta Tables). Exposure to Spark, Databricks, and data lake/lakehouse environments. Understanding of Agile development methods, CI/CD pipelines, GitHub, and automated testing. Practical experience More ❯

of Kubernetes, Docker, and cloud-native data ecosystems. Demonstrable experience with Infrastructure as Code tools (Terraform, Ansible). Hands-on experience with PostgreSQL and familiarity with lakehouse technologies (e.g. Apache Parquet, Delta Tables). Exposure to Spark, Databricks, and data lake/lakehouse environments. Understanding of Agile development methods, CI/CD pipelines, GitHub, and automated testing. Practical experience More ❯

pipelines and ETL processes. Proficiency in Python. Experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data modelling, warehousing, and optimisation. Familiarity with big data frameworks (e.g. Apache Spark, Hadoop). Understanding of data governance, security, and compliance best practices. Strong problem-solving skills and experience working in agile environments. Desirable: Experience with Docker/Kubernetes, streaming More ❯