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Job Description – Data Products 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

• Strong Clinical and Operational domain knowledge in Pharma (Life Science ) Industry
• Must have 3 to 5 years of experience with Python (or a similar language) and Data Engineering.
• Hands on experience with EMR
• Hands on experience with AWS ( Athena, Redshift)
• Hands on experience working with Snowflake
• Hands on experience with DataIku
• Good to have working exposure to Databricks
• Hands on experience with Dremio
• 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 and experience with dbt (data build tool) for implementing data transformations and quality checks.
• Big Data Ecosystem: Hands-on experience with PySpark and distributed processing frameworks, specifically on AWS EMR.
• Cloud Data Warehousing: Practical experience working with and optimizing large datasets in cloud data warehouses such as Amazon Redshift and/or Snowflake.
• 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

• Experience in the Pharmaceutical/Biotech industry, particularly with clinical or regulated data.
• Knowledge of data visualization tools (e.g., Tableau, Power BI).
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Bachelor's or master’s degree in computer science, Engineering, or a related field.

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