5 of 5 Apache Spark Jobs in Manchester

lead embedded data science teams, partnering effectively with senior stakeholders across multiple domains Hands‐on technical expertise with tools such as Databricks, Python, Spark, and GCP/BigQuery Engineering mindset, with experience moving teams toward machine learning engineering best practice Credibility to lead long‐tenured individual contributors while providing ...

scale. The position sits in a team delivering high-impact ML across marketing and advertising, working on both real-time and batch workloads with Spark, Python, Java, and #J-18808-Ljbffr ...

from ingestion and streaming through to warehousing, serving, and cost optimisation You have deep experience with streaming architectures – Kinesis, Kafka/MSK, Flink, or Spark Streaming – and know when each is the right choice You can model the cost implications of architecture decisions and advise clients on trade‐offs … between throughput, latency, durability, and spend AWS certification at professional or specialty level is strongly preferred Mastery of Python, SQL, and Spark – and strong opinions on how they should be used in production data pipelines Deep experience with dbt, Airflow, or equivalent orchestration – including how to build pipelines that ...

business use cases and/or to improve product/system performance, quality and accuracy. Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads. ML Infrastructure: Help build a first-class machine learning platform … learning on real recommendations use cases (brownie points for productionised sequential learning use cases!). Experience with ML/distributed ML frameworks like Ray, Spark-MLlib, TensorFlow etc. Experience with real-time scoring/evaluation of models with low latency constraints. Great coding skills and strong software development experience ...

business use cases and/or to improve product/system performance, quality and accuracy. Near Real‐Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads. ML Infrastructure: Help build a first‐class machine learning platform … learning on real recommendations use cases (brownie points for productionised sequential learning use cases). Experience with ML/distributed ML frameworks like Ray, Spark‐MLlib, TensorFlow etc. Experience with real‐time scoring/evaluation of models with low latency constraints. Great coding skills and strong software development experience ...