1 to 25 of 102 Apache Spark Jobs in Central London

Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis … years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF More ❯

Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis … years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF More ❯

Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis … years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF More ❯

Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis … years’ experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF More ❯

in consumer-facing or marketplace environments. Strong knowledge of distributed systems and modern data ecosystems, with hands-on experience using technologies such as Databricks, Apache Spark, Apache Kafka, and DBT. Proven success in building and managing data platforms supporting both batch and real-time processing architectures. Deep More ❯

in consumer-facing or marketplace environments. Strong knowledge of distributed systems and modern data ecosystems, with hands-on experience using technologies such as Databricks, Apache Spark, Apache Kafka, and DBT. Proven success in building and managing data platforms supporting both batch and real-time processing architectures. Deep More ❯

with cloud data platforms such as GCP (BigQuery, Dataflow) or Azure (Data Factory, Synapse) Expert in SQL, MongoDB and distributed data systems such as Spark, Databricks or Kafka Familiarity with data warehousing concepts and tools (e.g. Snowflake) Experience with CI/CD pipelines, containerization (Docker), and infrastructure-as-code More ❯

modelling (relational, NoSQL) and ETL/ELT processes. Experience with data integration tools (e.g., Kafka, Talend) and APIs. Familiarity with big data technologies (Hadoop, Spark) and real-time streaming. Expertise in cloud security, data governance, and compliance (GDPR, HIPAA). Strong SQL skills and proficiency in at least one More ❯

Flask, Django, or FastAPI. Proficiency in Python 3.x and libraries like Pandas, NumPy, and Dask. Experience with data manipulation and processing frameworks (e.g., PySpark, Apache Beam). Strong knowledge of databases, including SQL and NoSQL (e.g., PostgreSQL, MongoDB). Familiarity with ETL processes and tools such as Airflow or More ❯

team-oriented environment. Preferred Skills: Experience with programming languages such as Python or R for data analysis. Knowledge of big data technologies (e.g., Hadoop, Spark) and data warehousing concepts. Familiarity with cloud data platforms (e.g., Azure, AWS, Google Cloud) is a plus. Certification in BI tools, SQL, or related More ❯

Purview, or Informatica, including projects around lineage, cataloging, and quality rules. Strong hands-on development experience in SQL and Python, with working knowledge of Spark or other distributed data processing frameworks. Design, development and implementation of distributed data solutions using API and microservice-based architecture. Deep understanding of ETL More ❯

Purview, or Informatica, including projects around lineage, cataloging, and quality rules. Strong hands-on development experience in SQL and Python, with working knowledge of Spark or other distributed data processing frameworks. Design, development and implementation of distributed data solutions using API and microservice-based architecture. Deep understanding of ETL More ❯

platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem More ❯

platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem More ❯

Skills: x5 + experience with Python programming for data engineering tasks Strong proficiency in SQL and database management Hands-on experience with Databricks and Apache Spark Familiarity with Azure cloud platform and related services Knowledge of data security best practices and compliance standards Excellent problem-solving and communication More ❯

Skills: x5 + experience with Python programming for data engineering tasks Strong proficiency in SQL and database management Hands-on experience with Databricks and Apache Spark Familiarity with Azure cloud platform and related services Knowledge of data security best practices and compliance standards Excellent problem-solving and communication More ❯

solutions that support key firm initiatives. Build scalable and efficient batch and streaming data workflows within the Azure ecosystem. Apply distributed processing techniques using Apache Spark to handle large datasets effectively. Help drive improvements in data quality, implementing validation, cleansing, and monitoring frameworks. Contribute to the firm’s More ❯

solutions that support key firm initiatives. Build scalable and efficient batch and streaming data workflows within the Azure ecosystem. Apply distributed processing techniques using Apache Spark to handle large datasets effectively. Help drive improvements in data quality, implementing validation, cleansing, and monitoring frameworks. Contribute to the firm’s More ❯

Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us More ❯

Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us More ❯

various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models More ❯

various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models More ❯

in 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 More ❯

in 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 More ❯

including components like Azure Data Factory, Azure Data Lake Storage, Azure SQL, Azure DataBricks, HD Insights, ML Service etc. Good knowledge of Python and Spark are required. Experience in ETL & ELT Good understanding of one scripting language Good understanding of how to enable analytics using cloud technology and ML More ❯