1 to 25 of 111 Apache Jobs in the South East

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 ❯

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 ❯

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 ❯

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 ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and 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 ❯

hands-on when needed. Nice to haves Experience leading technical discovery or architecture definition in a scaling SaaS or fintech environment. Familiarity with event-driven or streaming architectures (Kafka, Apache Flink, etc.). Practical exposure to AI/LLM orchestration frameworks or fine-tuning workflows. Experience designing developer tools, data platforms, or intelligent systems. Interest in or experience mentoring More ❯

e.g., KDB, OneTick) and Parquet-based file storage to optimize data access and retrieval. Design scalable cloud-native solutions (AWS preferred) for market data ingestion and distribution. (Bonus) Integrate Apache Iceberg for large-scale data lake management and versioned data workflows. Collaborate with trading and engineering teams to define data requirements and deliver production-grade solutions. Implement robust data More ❯

e.g., KDB, OneTick) and Parquet-based file storage to optimize data access and retrieval. Design scalable cloud-native solutions (AWS preferred) for market data ingestion and distribution. (Bonus) Integrate Apache Iceberg for large-scale data lake management and versioned data workflows. Collaborate with trading and engineering teams to define data requirements and deliver production-grade solutions. Implement robust data More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code More ❯

and architecture. Skills & Experience Required: 2-5 years of software development experience. Strong hands-on expertise in Scala (mandatory) , plus Python and Java . Experience with Big Data frameworks ; Apache Spark experience is an advantage. Solid understanding of software engineering principles, data structures, and algorithms. Strong problem-solving skills and ability to work in an Agile environment. Educational Criteria More ❯

and architecture. Skills & Experience Required: 2-5 years of software development experience. Strong hands-on expertise in Scala (mandatory) , plus Python and Java . Experience with Big Data frameworks ; Apache Spark experience is an advantage. Solid understanding of software engineering principles, data structures, and algorithms. Strong problem-solving skills and ability to work in an Agile environment. Educational Criteria More ❯

data storytelling and operational insights. Optimise data workflows across cloud and on-prem environments, ensuring performance and reliability. Skills & Experience: Strong experience in ETL pipeline development using tools like Apache Airflow, Informatica, or similar. Advanced SQL skills and experience with large-scale relational and cloud-based databases. Hands-on experience with Tableau for data visualisation and dashboarding. Exposure to 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 ❯

Thrills Strong SQL skills, able to write complex and performant queries with ease. Solid experience in Python development for data workflows Experience building and maintaining ETL pipelines, ideally with Apache Airflow or a similar orchestration tool Hands-on experience with Google Cloud Platform (BigQuery, GCS, etc.) or another major cloud provider Good understanding of data modelling principles and the More ❯