end-to-end technical aspects of all data pipelines Support ETL processes including, data ingestion, transformation Document and effectively communicate data engineering processes and solutions. Bachelor's degree or higher Performance Computing, Data Warehousing, Big Data Processing Strong Experience working with various relational Hadoop, Kafka, Nifi or Spark or Cloud-based big data processing environments like Amazon Redshift, Google BigQuery
utilise advanced features for data visualisation and analysis. Automate processes using workflow middleware reporting capabilities and streamline data retrieval processes. Minimum Requirements Bachelors degree experience in BI Analytics. Data Analysis experience essential. Process Automation experience. Data Visualisation reporting capabilities and streamline data retrieval processes.
search of a BA that is skilled in analysing data, processes, and systems and identifying areas for improvement
of extensive experience in data migration, integration, and ETL processes Familiarity with modern data SQL and NoSQL data storage Familiarity with data processing frameworks like Snowflake, Databricks, or Apache
train and maintain models
and maintain scalable and efficient data pipelines and ETL processes to ingest, transform, and load data including data storage, data retrieval, and data processing for enhanced performance and scalability. ▪ ▪ Implement data quality and data governance processes to ensure accuracy, consistency, and integrity understanding of data modelling, data warehousing, and ETL processes. ▪ Comfortable working with cloud-based
Experience designing, building and maintaining data processing systems; Database design, data modelling and
Ability to train and maintain models Data cleaning and pre-processing (Size, data distribution, imputation and software engineering, financial services data processes, technical business intelligence. 5 - 7 years' images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data
to orchestrate and automate data workflows, ensuring seamless ETL processes. Utilize Databricks to perform both Azure and Python notebooks for scalable data processing. PowerBI - Transform raw data into compelling
of extensive experience in data migration, integration, and ETL processes. Familiarity with modern data SQL and NoSQL data storage. Familiarity with data processing frameworks like Snowflake, Databricks, or Apache parvana.co.uk Data Migration, Data Architecture, SQL, NoSQL, Python, ETL Processes