AWS Data Engineer

About the Role

As an AWS Data Engineer at Barclays, you will play a pivotal role in ensuring the resilience, scalability, and reliability of critical Digitized MI architecture within the Management Information reporting domain. Your primary focus will be on designing and building data pipelines, data warehouses, and data lakes to collect, store, process, and analyze data accurately, securely, and efficiently.

Key Responsibilities

• Design and build data architectures and pipelines that enable the transfer and processing of durable, complete, and consistent data.
• Develop and implement data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
• Collaborate with data scientists to build and deploy machine learning models.
• Develop processing and analysis algorithms fit for the intended data complexity and volumes.
• Work closely with BA, SA, Engineering teams, and stakeholders across multiple business divisions to deliver high-performing solutions through agile delivery models.
• Champion a data-driven and collaborative approach to ensure that performance considerations are embedded throughout the software development lifecycle.

Skills & Qualifications

• Experience in designing & building Astronomer/Airflow DAGs.
• Working knowledge of pySQL, pySpark for data processing.
• Python programming: pandas, boto3, PySpark for data processing.
• Design & Build MI solutions using different AWS Services (S3, EC2, IAM, Glue, Lambda, Step Functions, CloudFormation, ServiceCatalog).
• Power BI, Tableau, Pyspark, Pandas, Spark, Python, pySQL, Astronomer Airflow, boto3, dbt, snowflake, Immuta.
• Bachelor's degree in Computer Science, Information Technology, or related field.
• 0-0 years of experience in data engineering or a related field.

What You'll Learn

As an AWS Data Engineer at Barclays, you will have the opportunity to learn and grow in a dynamic and fast-paced environment. You will gain hands-on experience with designing and building data architectures, collaborating with data scientists, and working with various AWS services. Additionally, you will develop your skills in data processing, analysis, and machine learning, and learn to work in an agile delivery model.

Resume Tip

When applying for this role, make sure to highlight your experience with data engineering tools and technologies, such as Astronomer/Airflow, pySQL, pySpark, and AWS services. Also, be sure to emphasize your ability to work collaboratively with cross-functional teams and your experience with agile delivery models.