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Job Description –AWS Data Engineer
Objectives and Purpose
The Senior Data Engineer ingests, builds, and supports large-scale data architectures that serve multiple downstream systems and business users. This individual supports the Data Engineer Leads and partners with Visualization on data quality and troubleshooting needs.
The Senior Data Engineer will:
Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses.
Support development testing and maintenance of data pipelines and platforms, to enable data quality to be utilized within business dashboards and tools.
Create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes.
Your Key Responsibilities
Must have 3 to 5 years of experience with Python and Data Engineering.
Hands on experience with AWS ( Athena, Redshift)
Hands on experience with AWS Glue, Pyspark, Python
Hands on experience with AWS Lambda
Expert-level experience in creating/analyzing complex SQL and creating data pipelines, data modeling skills, and frameworks.
Expert-level experience in creating/analyzing complex SQL and creating data pipelines, data modeling skills, and frameworks.
Strong technical knowledge and extensive application support experience in systems and applications within clinical development
Problem-solving, analytical, quality mindset, and strong business acumen
Ability to translate complex business questions and requirements and develop effective solutions.
Understanding of clinical data standards
Excellent analytical skills
Detail-oriented, demonstrating good interpersonal and leadership skills, a team player.
Self-motivated, work effectively under pressure.
Effective verbal and written communication skills
Required Skills & Qualifications
Experience: 3-5 years of progressive experience in Data Engineering, Data Warehousing, or a related role.
Programming: Expertise in Python for data manipulation, scripting, and pipeline development.
Data Transformation: Strong proficiency with modern SQL
Big Data Ecosystem: Hands-on experience with PySpark and distributed processing frameworks, specifically on AWS Glue, Lambda, Pyspark
Cloud Data Warehousing: Practical experience working with and optimizing large datasets in cloud data warehouses such as Amazon Redshift
Cloud Storage: Experience with Amazon S3 for building and managing data lakes.
DevOps/CI/CD: Familiarity with CI/CD tools like Jenkins and source control systems, specifically Bitbucket (or similar like Git/GitHub/GitLab).
Methodology: Proven experience working effectively within an Agile - SCRUM development framework.
Communication: Exceptional written and verbal communication skills with the ability to influence and collaborate across teams.
Desired Skillsets
Knowledge of data visualization tools (e.g., Tableau, Power BI).
Familiarity with containerization technologies (e.g., Docker, Kubernetes).
Bachelors or master’s degree in computer science, Engineering, or a related field.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
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