1 to 25 of 46 Apache Spark Jobs in London

keys, sort keys , and workload management. Implement Redshift Spectrum to query data in S3 using external tables. 3. Data Lake & Iceberg Implement and maintain Apache Iceberg tables on AWS for schema evolution and ACID operations. Build Iceberg-based ingestion and transformation pipelines using Glue, EMR, or Spark. Ensure high … data Billing & revenue assurance Build models and pipelines to support network analytics, customer 360, churn prediction, fraud detection , etc. 7. Performance Optimization & Monitoring Tune Spark/Glue jobs for performance and cost. Monitor Redshift/Athena/S3 efficiency and implement best practices. Perform data quality checks and validation ...

platform, features, and best practices with Strong understanding of data modeling principles and techniques A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Knowledge of ETL/ELT processes ...

pragmatic, impact-focused way What You Bring Senior level Data Engineering experience Excellent Python and SQL skills Experience in big data environments (e.g., Spark, distributed systems, cloud data platforms) Solid understanding of data modeling, ETL/ELT, and pipeline architecture Willingness to work onsite in Edinburgh or London ...

practices, including ETL/ELT, data warehousing and data modelling. - Expertise in cloud data platforms, ideally Azure services such as Data Factory, Synapse, Databricks, Spark or Snowflake. - Proficiency in Python, SQL and other relevant languages for building pipelines and enabling automation. - Experience building and managing production data services, integrating ...

Strong full-stack experience with Python , Java (Spring Boot) , React , SQL, and relational databases. Hands-on experience with modern data engineering tools (e.g. Airflow, Spark, Kafka, dbt, Snowflake or similar). Experience with cloud platforms , containerisation (Docker/Kubernetes) , and CI/CD pipelines . Solid understanding of data ...

leading and developing data engineering platforms. The ideal candidate will possess hands-on expertise in the following areas: Extensive enterprise experience with Hadoop, Spark , and Splunk. Proficiency in object-oriented and functional scripting, particularly in Python . Skilled in handling raw, structured, semi-structured, and unstructured data ...

Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake ...

Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake ...

/or Computer Vision. Strong knowledge of Machine Learning algorithms and statistics. Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred). Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines. Preferred Skills:- Experience with LLMs/Generative AI (OpenAI, Hugging Face ...

about other roles, please contact Nick Mandella at Harnham. KEYWORDS Python, SQL, AWS, GCP, Azure, Cloud, Databricks, Docker, Kubernetes, CI/CD, Terraform, Pyspark, Spark, Kafka, machine learning, statistics, Data Science, Data Scientist, Big Data, Artificial Intelligence, private equity, finance. ...

commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative Culture ...

data modeling concepts and ETL/ELT processes. Ability to troubleshoot and optimize data workflows. Required Knowledge and Skills: Exposure to Databricks or Spark-based environments. Experience with data governance tools and practices. Experience with JavaScript Full-Stack development environments including MongoDB or similar NoSQL databases Knowledge of version ...

discussions and provide guidance on data engineering best practices. Ability to troubleshoot and optimize data workflows. Required Knowledge and Skills: Experience with Databricks or Spark-based environments, including optimization strategies. Familiarity with data governance tools and frameworks (e.g., Unity Catalog). Experience with JavaScript Full-Stack development environments including ...

sectors. Strong knowledge of data fabric architectures, metadata management, and data governance principles. Experience with SQL, ETL tools, and big data technologies (e.g., Hadoop, Spark, Kafka). Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and data integration frameworks. Strong problem-solving skills and ability to work ...

/CD (Azure DevOps/GitHub). Excellent communication with technical and non-technical stakeholders. Desired Skills Power BI/Tableau Stakeholder management Spark/Hadoop Unit testing frameworks Azure advanced analytics Data warehousing experience Azure Data Engineer certification Agile/Scrum/Kanban exposure This is a London ...

Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years in a software or data engineering role, with at least 3 years specifically focused on the deployment and scaling ...

able to engage technical and non-technical stakeholders Nice to Have: Experience with modern analytics and BI platforms Knowledge of big data technologies (e.g. Spark, Hadoop) Experience with real-time or event-driven architectures Familiarity with data cataloguing and lineage tools Experience working in regulated or data-sensitive environments ...

/Q or similar Experience with Airflow, Dagster or similar tools. Exposure to container technologies: Docker, Podman etc Knowledge of 'big data' technologies (Hadoop, Spark, Parquet) Experience with TAQ data, and exchange connectivity. Compensation Anticipated Salary Range for United States: $100,000 - $150,000 base salary, plus eligible ...

hedge fund, energy major or vendor serving these sectors. Knowledge of JavaScript frameworks, particularly React.js . Experience with Big Data technologies such as HDFS, Spark, Scala, Kudu, HBase, SQL, Impala , and traditional RDBMS. Quantitative skills in areas such as statistics, probability, optimization or derivative pricing. Some hands-on C++ ...

bank, hedge fund, energy major or vendor serving these sectors. Knowledge of JavaScript frameworks, particularly React.js. Experience with Big Data technologies such as HDFS, Spark, Scala, Kudu, HBase, SQL, Impala, and traditional RDBMS. Quantitative skills in areas such as statistics, probability, optimization or derivative pricing. Some hands-on C++ ...

DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process The process is fully structured, transparent, and efficient: Video call - high-level overview ...

DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process The process is fully structured, transparent, and efficient: Video call - high-level overview ...

Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar) Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers, or graph neural networks Exposure to model optimisation techniques (quantisation, distillation, efficient inference ...

models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation ...

from classical statistics and regression to deep learning and NLP. Data Engineering: Proficiency in SQL and experience working with modern data stacks (e.g., Snowflake, Spark, or cloud-native tools on AWS/GCP/Azure). Scientific Rigor: A strong foundation in the scientific methodforming hypotheses, designing experiments ...