1 to 25 of 67 Apache Spark Jobs in the South West

analytical, problem-solving, and critical thinking skills. 8.Experience with social media analytics and understanding of user behaviour. 9.Familiarity with big data technologies, such as Apache Hadoop, Apache Spark, or Apache Kafka. 10.Knowledge of AWS machine learning services, such as Amazon SageMaker and Amazon Comprehend. 11.Experience with More ❯

modelling, design, and integration expertise. Data Mesh Architectures: In-depth understanding of data mesh architectures. Technical Proficiency: Proficient in dbt, SQL, Python/Java, Apache Spark, Trino, Apache Airflow, and Astro. Cloud Technologies: Awareness and experience with cloud technologies, particularly AWS. Analytical Skills: Excellent problem-solving and More ❯

years, and ability to obtain security clearance. Preferred Skills Experience with cloud platforms (IBM Cloud, AWS, Azure). Knowledge of big data frameworks (Apache Spark, Hadoop). Experience with data warehousing tools like IBM Cognos or Tableau. Certifications in relevant technologies are a plus. Additional Details Seniority level More ❯

government security clearance. Preferred Technical And Professional Experience Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Familiarity with big data technologies (Hadoop, Spark). Background in data science, IT consulting, or a related field. AWS Certified Big Data or equivalent Seniority level Seniority level Mid-Senior level More ❯

visualization tools. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior analysis. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS ML services like SageMaker, Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to More ❯

statistical packages. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior analysis. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. More ❯

visualization tools. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior analysis. Familiarity with big data technologies like Hadoop, Spark, Kafka. Knowledge of AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. More ❯

and statistical packages. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior. Familiarity with big data technologies like Hadoop, Spark, Kafka. Knowledge of AWS ML services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention More ❯

and statistical packages. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior. Knowledge of big data tools like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. More ❯

statistical packages. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior analysis. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. More ❯

translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape More ❯

translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape More ❯

Azure) · Experience with: o Data warehousing and lake architectures o ETL/ELT pipeline development o SQL and NoSQL databases o Distributed computing frameworks (Spark, Kinesis etc ) o Software development best practices including CI/CD, TDD and version control. o Containerisation tools like Docker or Kubernetes o Experience More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

and statistical packages. Strong analytical and problem-solving skills. Experience with social media analytics and user behavior. Knowledge of big data tools like Hadoop, Spark, Kafka. Familiarity with AWS ML services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention More ❯

Jenkins, Bamboo, Concourse etc. Monitoring utilising products such as: Prometheus, Grafana, ELK, filebeat etc. Observability - SRE Big Data solutions (ecosystems) and technologies such as: Apache Spark and the Hadoop Ecosystem Edge technologies e.g. NGINX, HAProxy etc. Excellent knowledge of YAML or similar languages The following Technical Skills & Experience More ❯

or similar technologies. Strong proficiency in SQL and experience with data modelling concepts. Hands-on experience with Azure Synapse, including familiarity with Synapse SQL, Apache Spark pools, and data integration capabilities. Experience with ETL/ELT processes and tools such as Azure Data Factory. Solid understanding of cloud More ❯

excellence and be a person that actively looks for continual improvement opportunities. Knowledge and skills Experience as a Data Engineer or Analyst Databricks/Apache Spark SQL/Python BitBucket/GitHub. Advantageous dbt AWS Azure Devops Terraform Atlassian (Jira, Confluence) About Us What's in it for More ❯