RDBMS, NO-SQL and Big Data technologies. Data visualization – Tools like Tableau Big data – Hadoop eco-system, Distributions like Cloudera/Hortonworks, Pig and HIVE Data processing frameworks – Spark & Sparkstreaming Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase/Cassandra, MongoDB) Experience in cloud data eco More ❯
RDBMS, NO-SQL and Big Data technologies. Data visualization – Tools like Tableau Big data – Hadoop eco-system, Distributions like Cloudera/Hortonworks, Pig and HIVE Data processing frameworks – Spark & Sparkstreaming Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase/Cassandra, MongoDB) Experience in cloud data eco More ❯
data from diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies: Utilize big data technologies such as Spark, Kafka, and Flink for distributed data processing and analytics. Cloud Platforms: Deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging … for data manipulation and scripting. Strong understanding of data modelling concepts and techniques, including relational and dimensional modelling. Experience in big data technologies and frameworks such as Databricks, Spark, Kafka, and Flink. Experience in using modern data architectures, such as lakehouse. Experience with CI/CD pipelines and version control systems like Git. Knowledge of ETL tools and … deploying and managing data solutions. Strong problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues. SQL (for database management and querying) ApacheSpark (for distributed data processing) ApacheSparkStreaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least More ❯
below. AI techniques (supervised and unsupervised machine learning, deep learning, graph data analytics, statistical analysis, time series, geospatial analysis, NLP, sentiment analysis, pattern detection, etc.) Python, R, or Spark for data insights Data Bricks/Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML … SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (SparkStreaming) Data manipulation and wrangling techniques Development and deployment technologies (virtualisation, CI tools like Jenkins, configuration management with Ansible, containerisation with Docker, Kubernetes) Data More ❯
industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of $13+ billion. Spark - Must have Scala - Must Have Hive & SQL - Must Have Recent hands-on experience with Scala coding is required. Banking/Capital Markets Domain - Good to have Interview includes coding … test. Job Description: Scala/Spark • Good Big Data resource with the below Skillset: § Spark § Scala § Hive/HDFS/HQL • Linux Based Hadoop Ecosystem (HDFS, Impala, Hive, HBase, etc.) • Experience in Big data technologies, real time data processing platform (SparkStreaming) experience would be an advantage. • Consistently demonstrates clear and concise More ❯
industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of $13+ billion. Spark - Must have Scala - Must Have Hive & SQL - Must Have Recent hands-on experience with Scala coding is required. Banking/Capital Markets Domain - Good to have Interview includes coding … test. Job Description: Scala/Spark • Good Big Data resource with the below Skillset: § Spark § Scala § Hive/HDFS/HQL • Linux Based Hadoop Ecosystem (HDFS, Impala, Hive, HBase, etc.) • Experience in Big data technologies, real time data processing platform (SparkStreaming) experience would be an advantage. • Consistently demonstrates clear and concise More ❯
and understanding of current cyber security threats, actors and their techniques. Experience with data science, big data analytics technology stack, analytic development for endpoint and network security, and streaming technologies (e.g., Kafka, SparkStreaming, and Kinesis). Strong sense of ownership combined with collaborative approach to overcoming challenges and influencing organizational change. Amazon is More ❯
recovery process/tools Experience in troubleshooting and problem resolution Experience in System Integration Knowledge of the following: Hadoop, Flume, Sqoop, Map Reduce, Hive/Impala, Hbase, Kafka, SparkStreaming Experience of ETL tools incorporating Big Data Shell Scripting, Python Beneficial Skills: Understanding of: LAN, WAN, VPN and SD Networks Hardware and Cabling set-up experience More ❯
West Midlands, United Kingdom Hybrid / WFH Options
Experis
grade on-prem systems. Key Responsibilities: Design, develop, and maintain data pipelines using Hadoop technologies in an on-premises infrastructure. Build and optimise workflows using Apache Airflow and SparkStreaming for real-time data processing. Develop robust data engineering solutions using Python for automation and transformation. Collaborate with infrastructure and analytics teams to support operational data … enterprise security and data governance standards. Required Skills & Experience: Minimum 5 years of experience in Hadoop and data engineering. Strong hands-on experience with Python, Apache Airflow, and Spark Streaming. Deep understanding of Hadoop components (HDFS, Hive, HBase, YARN) in on-prem environments. Exposure to data analytics, preferably involving infrastructure or operational data. Experience working with Linux systems More ❯