26 to 50 of 199 Apache Spark Jobs in the UK

plus work experience BS & 5+ years of work experience MS & 4+ years of work experience Proficient with machine learning and statistics Proficient with Python, deep learning frameworks, Computer Vision, Spark Have produced production level algorithms Proficient in researching, developing, synthesizing new algorithms and techniques Excellent communication skills Desirable Qualifications Master's or PhD level degree 5+ years of work More ❯

driven decision-making. Responsibilities for the Senior Data Engineer: Design, build, and maintain scalable data pipelines and architectures, ensuring reliability, performance, and best-in-class engineering standards Leverage Databricks, Spark, and modern cloud platforms (Azure/AWS) to deliver clean, high-quality data for analytics and operational insights Lead by example on engineering excellence, mentoring junior engineers and driving … 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 More ❯

AI: Practical experience with Deep Learning frameworks (e.g., TensorFlow, PyTorch) for applications like NLP (Transformer models, BERT) or computer vision. Big Data Tools: Experience with big data platforms like Spark (PySpark) for handling large-scale datasets. MLOps: Familiarity with MLOps tools and concepts (e.g., Docker, Kubernetes, MLflow, Airflow) for model deployment and lifecycle management. Financial Domain Knowledge: Direct experience More ❯

able to work across full data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse design and data modelling - Experience managing Data Migration projects. - Cloud data platform development … the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) - Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of … other data tools and programming languages such as Python & Spark and Strong SQL experience. - Experience is building Data lake and building CI/CD data pipelines - A candidate is expected to understand and can demonstrate experience across the delivery lifecycle and understand both Agile and Waterfall methods and when to apply these. Experience: This position requires several years of More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects What we offer Equity options - share in More ❯

work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using More ❯

/ELT pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to create meaningful business impact. Soft Skills: Excellent More ❯

architecture. Familiarity with CI/CD and DevOps for data engineering. A detail-oriented mindset and strong problem-solving skills. Bonus Skills: Experience with big data tools (e.g., Hadoop , Spark ). Exposure to machine learning workflows . Understanding of prompt engineering concepts. Benefits: 25 days annual leave (plus bank holidays). An additional day of paid leave for your More ❯

data engineering. A detail-oriented mindset and strong problem-solving skills. Degree in Computer Science , Engineering , or a related field. Bonus Skills: Experience with big data tools (e.g., Hadoop , Spark ). Exposure to machine learning workflows . Understanding of prompt engineering concepts. Benefits: 25 days annual leave (plus bank holidays). An additional day of paid leave for your More ❯

troubleshoot data workflows and performance issues Essential Skills & Experience: Proficiency in SQL , Python , or Scala Experience with cloud platforms such as AWS, Azure, or GCP Familiarity with tools like Apache Spark , Kafka , and Airflow Strong understanding of data modelling and architecture Knowledge of CI/CD pipelines and version control systems Additional Information: This role requires active SC 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 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 More ❯

practices such as testing, version control, and CI/CD Hands-on experience building scalable data pipelines in a modern cloud environment (e.g., dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of More ❯

and delivering end-to-end AI/ML projects. Nice to Have: Exposure to LLMs (Large Language Models), generative AI , or transformer architectures . Experience with data engineering tools (Spark, Airflow, Snowflake). Prior experience in fintech, healthtech, or similar domains is a plus. More ❯

observability. Preferred Qualifications Exposure to machine learning workflows, model lifecycle management, or data engineering platforms. Experience with distributed systems, event-driven architectures (e.g., Kafka), and big data platforms (e.g., Spark, Databricks). Familiarity with banking or financial domain use cases, including data governance and compliance-focused development. Knowledge of platform security, monitoring, and resilient architecture patterns. About us 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 ❯

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 ❯

e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge of DevOps technologies such as Docker and Terraform and ML Ops practices and platforms like ML Flow Have experience with agile delivery methodologies and CI/CD More ❯

big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash) and dashboarding (Tableau, Looker) Domain experience in forecasting, optimisation, or geospatial analytics We would like to talk to you if you More ❯

big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash) and dashboarding (Tableau, Looker) Domain experience in forecasting, optimisation, or geospatial analytics We would like to talk to you if you More ❯