Let's do this. Let's change the world. In this vital role as Data Engineer at Amgen you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes
Design, develop, and optimize data pipelines/workflows using Databricks (Spark, Delta Lake) for ingestion, transformation, and processing of large-scale data. A knowledge of Medallion Architecture will be an added advantage.
Build ETL pipeline with Informatica or other ETL tools.
Support data governance and metadata management.
Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
Identify and resolve complex data-related challenges
Adhere to best practices for coding, testing, and designing reusable code/component
Analyze business and technical requirements and begin translating them into simple development tasks
Execute unit and integration tests, and contribute to maintaining software quality
Identify and fix bugs and defects during development or testing phases
Contribute to the maintenance and support of applications by monitoring performance and reporting issues
Use CI/CD pipelines as part of DevOps practices and assist in the release process
What we expect of you
We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications:
Master's/Bachelor's degree and 4 to 8 years of Computer Science, IT or related field experience
Preferred Qualifications:
Experience with Software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
Knowledge of Python/R, Databricks, cloud data platforms
Strong understanding of data governance frameworks, tools, and best practices.
Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
Must-Have Skills:
Bachelor's or master's degree in computer science, Data Science, or a related field.
Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), python for workflow orchestration, performance tuning on big data processing
Proficiency in data analysis tools (eg. SQL)
Proficient in SQL for extracting, transforming, and analyzing complex datasets from relational data stores
Strong programming skills in Python, PySpark, and SQL.
Familiarity with Informatica and/or other ETL tools.
Experience working with cloud data services (Azure, AWS, or GCP).
Strong understanding of data modeling, entity relationships
Professional Certifications
AWS Certified Data Engineer (preferred)
Databricks Certificate (preferred)
Soft Skills:
Excellent problem-solving and analytical skills
Strong communication and interpersonal abilities
High attention to detail and commitment to quality
Ability to prioritize tasks and work under pressure
Team-oriented with a proactive and collaborative mindset
Willingness to mentor junior developers and promote best practices
* Adaptable to changing project requirements and evolving technology
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