Senior Data Engineer (AWS)

Position Overview:
Our client is seeking a Senior Data Engineer to expand and optimize their Data & Analytics platform. In this pivotal role, you'll drive the ingestion, transformation, and provisioning of data, empowering their Insights teams to extract actionable insights efficiently. Your expertise will not only enhance current capabilities but also foster a culture of data-driven innovation, aligned closely with our rigorous data governance practices.

The Opportunity:
You will design, build, and maintain scalable and reliable data pipelines using AWS technologies (e.g. Glue, Redshift, and Athena), integrating data from various sources to ensure seamless and efficient data flow throughout the organization. Developing and implementing ETL processes, you'll transform raw data into meaningful insights while managing and optimizing data storage solutions, including data lakes and data warehouses, to support large-scale data analysis.

You will ensure data accuracy, completeness, and consistency through robust data quality checks and adherence to data governance best practices. You'll monitor and optimize the performance of data pipelines and storage solutions to ensure low latency and high availability. Collaborating with data scientists, analysts, and other stakeholders, you'll understand data needs and deliver high-quality data solutions, automating repetitive tasks and data workflows to improve efficiency and reduce manual intervention.

Additionally, you'll implement data security measures to protect sensitive information and comply with regulatory requirements, maintaining comprehensive documentation of data processes, pipelines, and architectures for reference and knowledge sharing.

Requirements:
Between 6-8 years of experience in Modern Data Platforms (AWS, Azure, etc.) and Data Engineering, combined with strong Agile delivery skills and a degree in Computer Science, Data Science, IT, or a related field. Extensive experience in AWS architecture, technologies, and services, along with the capability to recommend new AWS services or solutions, is essential. Candidates must possess proficiency in SQL, Python, Athena, Redshift, and Glue for data engineering tools and languages. A strong understanding of Data & Analytics concepts and technologies, including data warehousing, data lakes, ETL, visualization, and reporting, with a focus on creating business value, is crucial. Additionally, candidates should have deep knowledge of Data Architecture, Data Modeling, Data Marts, and Metadata Management best practices.