21 of 21 Permanent Apache Spark Jobs in Berkshire

and contribute to technical roadmap planning Technical Skills: Great SQL skills with experience in complex query optimization Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark) Hands-on experience building and maintaining data ingestion pipelines Proven track record of optimising queries, code, and system performance Experience with open-source data processing frameworks (Apache Spark, Apache Kafka, Apache Airflow) Knowledge of distributed computing concepts and big data technologies Experience with version control systems (Git) and CI/CD practices Experience with relational databases (PostgreSQL, MySQL or similar) Experience with containerization technologies (Docker, Kubernetes) Experience with data orchestration tools (Apache Airflow or Dagster) Understanding of data warehousing concepts and dimensional More ❯

staying current with emerging data technologies. Technical Requirements Proficiency in SQL , including complex query design and optimisation. Strong Python programming skills, particularly with libraries such as pandas , NumPy , and Apache Spark . Experience building and maintaining data ingestion pipelines and optimising performance. Hands-on experience with open-source data frameworks such as Apache Spark , Apache Kafka , or Apache Airflow . Knowledge of distributed computing and big data concepts. Experience using version control systems (Git) and CI/CD practices. Familiarity with relational databases (PostgreSQL, MySQL, or similar). Experience with containerisation technologies ( Docker , Kubernetes ). Understanding of data orchestration tools (e.g., Airflow or Dagster). Knowledge of data warehousing principles and dimensional modelling More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and … automation pipelines. Experience working with relational databases such as PostgreSQL, MySQL, or equivalent platforms. Skilled in using containerization technologies including Docker and Kubernetes. Experience with workflow orchestration tools like Apache Airflow or Dagster. Familiar with streaming data pipelines and real-time analytics solutions. More ❯

us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role We are looking for a skilled Spark/Scala Developer to join our data engineering team. The ideal candidate will have hands-on experience in designing, developing, and maintaining large-scale data processing pipelines using Apache Spark and Scala. You will work closely with data scientists, analysts, and engineers to build efficient data solutions and enable data-driven decision-making. Key Responsibilities: Develop, optimize, and maintain data pipelines and ETL processes using Apache Spark and Scala. Design scalable and robust data processing solutions for batch and real-time data. Collaborate with cross … functional teams to gather requirements and translate them into technical specifications. Perform data ingestion, transformation, and cleansing from various structured and unstructured sources. Monitor and troubleshoot Spark jobs, ensuring high performance and reliability. Write clean, maintainable, and well-documented code. Participate in code reviews, design discussions, and agile ceremonies. Implement data quality and governance best practices. Stay updated with More ❯

Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid 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 ❯

modern data platforms (Databricks, Snowflake, Kafka), container orchestration (Kubernetes/OpenShift), and multi-cloud deployments across AWS, Azure, GCP Advanced knowledge of Big Data ecosystems (Hadoop/Hive/Spark), data lakehouse architectures, mesh topologies, and real-time streaming platforms Strong Unix/Linux skills, database connectivity (JDBC/ODBC), authentication systems (LDAP, Active Directory, OAuth2), and data integration More ❯

GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins or GitHub More ❯

a focus on having delivered in Microsoft Azure Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London More ❯

fine-tuning, or deployment. Technical Skills: Proficiency in Python and frameworks such as PyTorch , TensorFlow , or JAX . Strong familiarity with distributed computing and data engineering tools (e.g., SLURM , Apache Spark , Airflow ). Hands-on experience with LLM training, fine-tuning, and deployment (e.g., Hugging Face , LLamafactory , NVIDIA NeMo ). Preferred Qualifications Advanced degree (MS/PhD) in More ❯

testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. More ❯

Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with relational databases and data processing and query engines (Spark, Trino, or similar). Familiarity with monitoring, observability, and alerting systems for production ML (Prometheus, Grafana, Datadog, or equivalent). Understanding of ML concepts. You don't need to More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯

in Python for data pipelines, transformation, and orchestration. Deep understanding of the Azure ecosystem (e.g., Data Factory, Blob Storage, Synapse, etc.) Proficiency in Databricks (or strong equivalent experience with Apache Spark ). Proven ability to work within enterprise-level environments with a focus on clean, scalable, and secure data solutions. If you are the right fit - contact me More ❯

science solutions in a commercial setting. MSc in Computer Science, Machine Learning, or a related field. Experience building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert More ❯

to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. More ❯

deep learning architectures (e.g., attention 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, and retrieval systems. Familiarity with large More ❯

assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

technologists, and analysts to enhance the quality, timeliness, and accessibility of data. Contribute to the evolution of modern cloud-based data infrastructure , working with tools such as Airflow, Kafka, Spark, and AWS . Monitor and troubleshoot data workflows, ensuring continuous delivery of high-quality, analysis-ready datasets. Play a visible role in enhancing the firm’s broader data strategy … ability in Python (including libraries such as pandas and NumPy ) and proficiency with SQL . Confident working with ETL frameworks , data modelling principles, and modern data tools (Airflow, Kafka, Spark, AWS). Experience working with large, complex datasets from structured, high-quality environments — e.g. consulting, finance, or enterprise tech. STEM degree in Mathematics, Physics, Computer Science, Engineering, or a More ❯

team leadership and upskilling responsibilities. Key Responsibilities Build and maintain Databricks Delta Live Tables (DLT) pipelines across Bronze → Silver → Gold layers, ensuring quality, scalability, and reliability. Develop and optimise Spark (PySpark) jobs for large-scale distributed processing. Design and implement streaming data pipelines with Kafka/MSK, applying best practices for late event handling and throughput. Use Terraform and … role) Mentor and upskill engineers, define coding standards, and embed engineering excellence across the team. What’s Expected Proven experience delivering end-to-end data pipelines in Databricks and Spark environments. Strong understanding of data modelling, schema evolution, and data contract management. Hands-on experience with Kafka, streaming architectures, and real-time processing principles. Proficiency with Docker, Terraform, and More ❯

ll do Lead the architecture and evolution of large scale streaming and backend systems, ensuring they are resilient, performant, and future-ready Apply deep knowledge of technologies such as Apache Flink, Kafka, and Spark to design reliable data pipelines and event driven systems Leverage your experience with modern backend languages such as Java, Scala, or Go to build … the curve What we’re looking for Experience operating at Staff Engineer or Principal Engineer level for atleast 2 years Expertise in streaming platforms such as Flink, Kafka, and Spark, with experience designing large-scale event driven architectures Strong background in backend engineering with one or more modern languages Ability to communicate complex technical concepts clearly to both engineers More ❯