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 ❯
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 ❯