1 to 25 of 351 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 ❯

and Snowflake Marketplace. Familiarity with Snowpark for Python/Java-based transformations. Understanding of role-based access control, data masking, and time travel features. Databricks: Hands-on experience with Apache Spark and Databricks Runtime. Proficiency in Delta Lake for ACID-compliant data lakes. Experience with Structured Streaming and Auto Loader. Familiarity with MLflow, Feature Store, and Model Registry. Use More ❯

Strong programming and integration skills: Java, JUNIT, REST services, DQL, SQL, GWT Proficiency in XML, XSD, xDB, XSL Operating systems: Linux and Windows Web and directory services: Apache HTTPD, Tomcat, Apache DS DevOps tools: Git, Jenkins, SonarQube, Bitbucket, Octopus More ❯

Snowflake, Databricks) Strong DevOps mindset with experience in CI/CD pipelines, monitoring, and observability tools (Grafana or equivalent). Exposure to analytics, reporting, and BI tools such as Apache Superset, Lightdash or OpenSearch Willingness to work across the stack by contributing to API development and, at times, UI components (Vue.js, Zoho, or similar). Excellent communication and collaboration 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 ❯

data quality, or other areas directly relevant to data engineering responsibilities and tasks Proven project experience developing and maintaining data warehouses in big data solutions (Snowflake) Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯

in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

Data warehouse operations and tunning experience in schema evolution, indexing, partitioning. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

systems. Nice to haves: Experience with NoSQL databases (MongoDB, Cassandra, Redis). Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Experience working with AI-driven development tools such as Cursor, Copilot, or More ❯

Linux-based, concurrent, high-throughput, low-latency software systems Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster) Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases Have a Bachelor or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience For more information about DRW's processing activities More ❯

the first time, Dev10 equips you with the tools to succeed. You'll train in technologies including Relational and Non-Relational Databases, APIs, Python, Pandas, Excel, Dash, Kafka, Airflow, Apache Spark, and Machine Learning. Now hiring for our Data Engineer cohort starting January 2026. To apply, please submit a formal application through our website: Dev10 Apply Here What We More ❯

frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but would be beneficial: Data Orchestration Tools: Familiarity with modern workflow management tools like Apache Airflow, Prefect, or Dagster Modern Data Transformation: Experience with dbt (Data Build Tool) for managing the transformation layer of the data warehouse BI Tool Familiarity : An understanding of how More ❯