Overview

• Ability to design database structure and experience in SQL programming language
• Experience in data modelling, data cleansing and ETLs (extract, transform and loads)
• Experience in data integration tool such as SSIS
• Familiarity with Tableau like Business Intelligence tool
• Understanding of Insurance and pensions domain
• Experience in Agile working
  
  

Key Responsibilities

• Design and implement data models to ensure high data integrity.
• Build and maintain efficient ETL pipelines for data extraction, transformation, and loading.
• Optimize data storage solutions for performance and scalability.
• Work with data scientists to define data requirements and ensure access to necessary data.
• Collaborate with IT teams to ensure infrastructure is aligned with data storage and processing requirements.
• Implement data governance and compliance measures to safeguard data security.
• Monitor and troubleshoot data pipeline systems to ensure reliability.
• Document data engineering processes and architectures for future reference.
• Keep up to date with emerging technologies and trends in data engineering.
• Automate repetitive tasks using scripting languages.
• Evaluate and recommend tools and technologies for data management purposes.
• Participate in system design reviews to ensure data integration effectiveness.
• Provide support for data-related incident resolution and troubleshooting.
• Conduct performance tuning of existing data processes.
• Contribute to the establishment of best practices for data engineering.
  
  

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in data engineering or a related role.
• Strong proficiency in SQL and relational databases.
• Experience with big data technologies such as Hadoop, Spark, or similar frameworks.
• Knowledge of cloud platforms like AWS, Azure, or Google Cloud.
• Proficiency in programming languages such as Python or Java.
• Experience in designing and implementing data warehouses.
• Familiarity with data pipeline tools such as Apache Airflow or similar.
• Understanding of data architecture best practices.
• Experience with data visualization tools is a plus.
• Knowledge of data governance and data quality frameworks.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• Ability to work in fast-paced environments and manage multiple priorities.
• Familiarity with version control systems like Git.
  
  

Skills: sql,java,google cloud,cloud,sql proficiency,data modeling,data quality,azure,data engineering,data cleansing,ssis,data integration,etl,python,cloud technologies,hadoop,tableau,aws,data governance,integration,apache airflow,spark,data modelling,data warehousing