AWS Data Engineer
Listed on 2026-09-26
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IT/Tech
Data Engineering, Data Warehousing, Data Analyst, Database Administrator
Tasks
AWS Data Engineer
Location:
London
Type : 3 days per week onsite hybrid mode
Duration: 3 months
Required Experience-10-15yrs
Job Overview
We are seeking a skilled and experienced Data Engineer to join our dynamic team. In this role, you will be responsible for developing, testing, improving, and maintaining new and existing databases to help users retrieve data effectively. As a data engineer, you will work closely with our data team to optimize our data systems and pipeline architecture, develop set processes for data mining, data modeling, and data production.
The ideal candidate should be an analytical problem solver, have a deep understanding of data relationship complexities, and be able to strategize and implement database solutions that support and enhance our company's data systems and data quality.
Responsibilities
Develop, construct, test, and maintain architectures such as databases and large-scale processing systems.
Discover opportunities for data acquisition and new uses for existing data.
Develop data set processes for data modeling, mining, and production.
Employ a variety of languages and tools to marry systems together or try to hunt down opportunities to acquire new data from other systems.
RequirementsRequired Skills
Proficiency in SQL and No
SQL databases.
Strong knowledge of Python, Java, or Scala.
Experience with data pipeline and workflow management tools.
The candidate must have a Bachelor's degree in Computer Science, Software Engineering, or a related field. A Master's degree or further education in Data Science or a related field is preferred.
Preferred Skills
Familiarity with cloud services like AWS, Google Cloud, or Azure.
Experience with big data tools:
Hadoop, Spark, Kafka, etc.
Knowledge of data integration tools like Informatica, Talend, etc.
Understanding of machine learning algorithms and statistics.
Experience with data visualization tools like Tableau, PowerBI, etc.
Knowledge of data warehousing solutions and ETL tools.
Familiarity with data architecture and data modeling techniques.
Experience with stream-processing systems:
Storm, Spark-Streaming, etc.
Knowledge of software development methodologies like Agile/Scrum.
Understanding of data privacy and governance.
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