1 to 25 of 49 Apache Spark Jobs in London

Design, build, and maintain cloud-based infrastructure using AWS Develop and manage Infrastructure as Code using Terraform Support and optimise data processing pipelines using Apache Spark and Airflow Collaborate with cross-functional teams to deliver secure and scalable solutions Implement CI/CD pipelines using GitLab Containerise applications … Notebooks for data exploration and development Key Skills & Experience Strong experience with AWS services Expertise in Terraform (Infrastructure as Code) Hands-on experience with: Apache Spark Python Apache Airflow Docker GitLab CI/CD Experience with security scanning tools such as: Trivy Trend Micro Wiz (or similar ...

Warehouses. Design and oversee ingestion frameworks for enterprise data sources, including: Microsoft SQL Server (on-premises and Azure SQL) Oracle Databases Develop and optimize Apache Spark workloads using PySpark or Scala, ensuring performance, scalability, and operational efficiency. Assess existing or partially completed data platform implementations and provide remediation … integration with Databricks SQL Warehouses Experience integrating enterprise data sources such as: Microsoft SQL Server (on-premises and Azure SQL) Oracle Databases Strong Apache Spark expertise using PySpark and/or Scala, including performance tuning, partitioning strategies, and workload orchestration. Experience evaluating and remediating incomplete, underperforming, or legacy ...

will be undertaking a monumental Transformation to unlock organisational pace and Data agility, moving to a scalable Cloud Data architecture centred around AWS Glue (Apache Spark) & Apache Airflow, with a key focus on re-engineering numerous complex Data pipelines to the new framework by leveraging Agentic … code generation in regulated environments Strong hands-on experience with AWS ecosystem: AWS Glue, S3, and related data platforms (e.g. Snowflake) Strong experience with Apache Airflow and DAG-based orchestration Experience designing configuration-driven frameworks: Using YAML or JSON Experience building automated testing for data pipelines: Functional equivalence testing ...

data engineering tasks. Experience with cloud platforms such as: AWS, Azure, Google Cloud Platform (GCP) Hands-on experience with data technologies such as: Apache Spark, Databricks, Kafka, Airflow, Snowflake, Hadoop ecosystems Experience designing and maintaining data warehouses and data lakes. Knowledge of DevOps and CI/CD tooling ...

subscription platforms, ad tech, and social media. Proven ability to automate and optimise data workflows , using modern ETL/ELT tools (e.g., Airflow, dbt, Apache Spark) to ensure timely and reliable delivery of data. Experience building robust data models and reporting layers to support performance dashboards, user engagement … hands-on experience in a data engineering role. Tools & Technologies : Databases : Proficient in SQL databases. Workflow Management Tools : Experience with orchestration platforms such as Apache Airflow . Programming Languages : Skilled in one or more of the following languages, i.e.: Python , Java , Go. Cloud Infrastructure : Strong understanding of cloud infrastructure ...

models are always running, always accurate, and always improving. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend Circadia’s ML pipeline orchestration using Apache Airflow, including training, evaluation, and deployment workflows. Build and maintain automated pipelines for model retraining, validation, and promotion across development, staging, and production environments. … closely related infrastructure role. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ML pipeline orchestration tools, particularly Apache Airflow. Experience with model registries and experiment tracking platforms (MLflow preferred). Experience deploying and operating ML workloads on AWS (Batch ...

understand where traditional patterns remain appropriate - and where modern approaches add measurable value. Data Engineering & Platform Understanding: Strong knowledge of distributed processing (e.g. Apache Spark). Familiarity with Hadoop ecosystem components. Working knowledge of SQL and NoSQL technologies. Understanding of ETL/ELT design trade-offs. Awareness ...

skills and understanding of modern data engineering principles. Desirable Skills Python and PySpark development. AWS services including EMR, S3, Lambda, Athena, and Redshift. Apache Spark and large-scale batch processing. Terraform, CI/CD pipelines, and Infrastructure as Code. Git/GitLab and modern software development practices. ...

years (Senior) of data engineering experience Hands-on experience with Palantir Foundry and/or Foundry Data Platform (FDP) Strong proficiency in: Python SQL Spark (PySpark or SparkSQL) Experience building production data pipelines in cloud environments (AWS, Azure, or GCP) Understanding of data modeling, schema design, and metadata management ...

Collaborate with senior developers and quantitative teams on new analytics capabilities Participate in debugging, testing, and production support activities Technology Environment Python Databricks/Apache Spark SQL Pandas/NumPy Git REST APIs Cloud technologies (Azure or AWS) Numerix (or equivalent pricing/risk platform) Jupyter/notebook … commercial Python development experience Strong understanding of data structures and software engineering fundamentals Experience working with data engineering or analytics tooling Exposure to Databricks, Spark, or cloud-based data platforms Understanding of SQL and relational databases Excellent problem-solving and communication skills STEM or Computer Science degree preferred Nice ...

with Airflow, Dagster or other orchestration tools Experience with data lakes (Synapse, Snowflake) Experience with Docker Experience with streaming technologies (Kafka, RabbitMQ) Experience with Spark or other big-data tools Hybrid working – 3 days per week in a central London office (Tues - Thurs) If you’re excited ...

capacity planning, skills development, and vendor contributions The individual: Expertise in Azure data services (ADLS, ADF, Databricks, Synapse, Event Hub/Kafka), Python, SQL, Spark/PySpark. Experience with data modeling, metadata and lineage tooling; performance & cost optimization. Proven leadership in engineering teams; Agile/DevOps ways of working ...

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 ...

strong focus on scalability, resilience, and performance. Develop and optimise scalable data pipelines , supporting both batch and streaming workloads, using technologies such as Apache Spark . Work extensively with data technologies , leveraging Python and SQL to deliver high-quality analytical and data-driven solutions. Lead the design ...

experience with SQL and data modelling concepts Strong analytical and problem-solving skills Nice to Have Skills Experience with data pipeline tools (Airflow, Kafka, Spark) Knowledge of cloud platforms (AWS, Azure or GCP) Familiarity with relational and NoSQL databases Additional programming experience (Python, Scala) Essential Requirements Active SC Clearance ...

Cloud engineering: Azure (preferred) and/or AWS/GCP; Kubernetes/Docker; serverless (Azure Functions/Lambda); secure networking/IAM. Data engineering: Spark/Databricks, ETL/ELT pipelines; integration with client data sources and enterprise systems; runbooks and operational handover. Product delivery: workshop facilitation, PRDs, user ...

improve data engineering processes. Mentor junior engineers and support knowledge-sharing across teams. Key Responsibilities: Design, build, and maintain scalable data pipelines using Databricks, Spark, and Delta Lake. Develop efficient ETL/ELT workflows to process large volumes of structured and unstructured data. Implement data governance, security, and compliance … data pipeline deployment and monitoring. What We Are Looking For: 5+ years of experience in data engineering or related roles. Strong expertise in Databricks, Spark, Delta Lake, and cloud data platforms (AWS, Azure, or GCP). Proficiency in Python and SQL for data manipulation and transformation. Experience with ...

looking for Strong Python + SQL (essential) 5+ years in data engineering/platform engineering AWS experience in production data environments Hands-on with Spark/Kafka/Snowflake/Databricks (or similar) Experience with data lakes/lakehouse/distributed systems Background in financial services, trading, or quantitative ...

scalable data pipelines, managing large datasets, and enabling engineering and AI teams to deliver high-performance data-driven products. Key Technical Requirements • Python • SQL • Spark • Airflow • Data pipelines • AWS or GCP Experience Required • 4+ years in data engineering • Experience working with large-scale structured and unstructured datasets • Strong ...

through influence with strong collaborator engagement skills. Preferred Experience Digital Twin, asset virtualization, or industrial data platforms Graph technologies (e.g., Neo4j), big data ecosystems (Spark, Hive, Hadoop) Databricks, Python, and modern analytics platforms Delivery of data products at enterprise scale Key Competencies Strategic product thinking with strong execution bias ...

Senior Data Engineer (Scala/Spark) London | Hybrid Working | Initial 12 month contract | £450-550pd PAYE + holiday pay We are partnering with a world-leading technology organisation seeking an experienced Senior Data Engineer to join a high-performing engineering team responsible for building and operating large-scale … machine learning workflows at scale. As a Senior Data Engineer, you will design, build and operate large-scale batch data pipelines using Scala and Apache Spark. Working alongside Machine Learning Engineers, Researchers and Platform Engineers, you will help develop the infrastructure and tooling required to process vast datasets ...

internal knowledge Competencies and Behaviours: 3+ years experience in data platform engineering, cloud engineering, or similar roles Strong hands-on experience with Databricks, including Apache Spark, Delta Lake, Workflows Proven experience designing and deploying data platforms on AWS and/or Azure (e.g. ADLS, S3, VNet/ ...

bring: Strong SQL + ETL/ELT experience Knowledge of Python/T-SQL Exposure to cloud platforms (Azure preferred) Nice to have: Databricks, Spark, CI/CD, big data This is a great opportunity to join a high-impact data team in a global organisation and shape ...

Prometheus, ElasticSearch , Grafana, OpenTelemetry ) for metrics, logs and traces Platform Technologies & BSS Vendor Platforms - Open source workflow engines (Temporal) - Stream/batch processing (Flink, Spark) - Test automation: Robot Framework and BDD - can review BDD robot files - BSS vendor platforms: Salesforce, Amdocs, Ciena - BSS/OSS proficiency: awareness of Product ...

Docker and Kubernetes is a plus. Experience designing end to end ML data pipelines. Experience with database technologies such as PostgreSQL, MySQL, or MongoDB, Spark, Databricks and stream data processing such as Kafka, RedPanda is a plus. Direct experience in building and applying large-scale (100M+ users) machine learning ...