Amgen
Biotechnology
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Amgen. Skills: Databricks, Apache Spark, PySpark, SparkSQL, SQL, Python, Data Pipeline Development, ETL/ELT Processes, Big Data Technologies, Cloud Platforms (AWS preferred). Designing, building, maintaining, analyzing, and interpreting data. Developing reports”
What You'll Achieve.
Provide actionable insights that drive business decisions; Ensure data is accessible, reliable, and efficiently managed; Meet fast-paced business needs across geographic regions; Deliver on shared objectives
Industry & Context.
Excellent problem-solving skills; Excellent critical-thinking and problem-solving skills; Identify and resolve complex data-related challenges
Work a later shift and may be assigned a second or third shift schedule, Willing and able to work during evening or night shifts, as required based on business requirements
What They're Looking For.
Must Have
Bachelor's / Master's degree in Computer Science, IT or related field, 8 to 13 years of experience in Computer Science, IT or related field, Hands-on experience with big data technologies and platforms, Experience with Databricks, Apache Spark (PySpark, SparkSQL), Experience with workflow orchestration, Experience with performance tuning on big data processing, Proficiency in data analysis tools (e.g. SQL), Experience with data visualization tools, Excellent problem-solving skills, Ability to work with large, complex datasets, Understanding of data governance frameworks, tools, and best practices
Nice to Have
Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA) processing, Experience with ETL tools such as Apache Spark, Experience with various Python packages related to data processing, Experience with machine learning model development, Understanding of data modeling, data warehousing, and data integration concepts, Knowledge of Python/R, Knowledge of Databricks, Knowledge of SageMaker, Knowledge of cloud data platforms, Experience implementing automated orchestration and monitoring of data pipelines using Databricks Jobs, Apache Airflow, or similar workflow tools, Familiarity with performance optimization techniques for big data processing, such as Spark job tuning, caching, partitioning, and indexing, Exposure to multi-source integration involving APIs, SQL databases, and cloud storage platforms, Demonstrated ability to collaborate across global teams and time zones, ensuring alignment and delivery in distributed environments, Certified Data Engineer (preferred on Databricks or cloud environments)
What You'll Do.
and interpreting data
Supporting and executing data governance initiatives
and maintaining data solutions for data generation
Assisting in design and development of the data pipeline
Creating data pipelines and ensuring data quality by implementing ETL processes
Contributing to the design
and implementation of data pipelines
and data integration solutions
Taking ownership of data pipeline projects from inception to deployment
Developing and maintaining data models
and other documentation
Implementing data security and privacy measures
Leveraging cloud platforms (AWS preferred) to build scalable and efficient data solutions
Designing and developing data pipelines leveraging Databricks
Engineering solutions for both structured and unstructured data
Implementing automated workflows for data ingestion
and deployment using Databricks Jobs and notebooks
Applying performance optimization techniques
Building integrations with multiple data sources
Identifying and resolving complex data-related challenges
Adhering to best practices for coding
and designing reusable code/component
Exploring new tools and technologies to improve ETL platform performance
Participating in sprint planning meetings and providing estimations on technical implementation
Implementing automated orchestration and monitoring of data pipelines
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs; Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines; Collaborate and communicate effectively with product teams; Collaborate effectively with global teams across time zones to maintain alignment, resolve issues, and deliver on shared objectives; Demonstrated awareness of how to function in a team setting
Communication Scope
Excellent communication skills; Collaborate and communicate effectively with product teams
Process & Methodology
Take ownership of data pipeline projects from inception to deployment, Manage scope, timelines, and risks
Full Job Description
## **Career Category** Information Systems ## ## **Job Description** _ABOUT AMGEN_ Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. _ABOUT THE ROLE_ _Role Description:_ The role is 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 governance 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 _Roles & Responsibilities:_ * Design, develop, and maintain data solutions for data generation, collection, and processing * Be a key team member that assists in design and development of the data pipeline * Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems * Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions * Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks * Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs * Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency * Implement data security and privacy measures to protect sensitive data * Leverage cloud platforms (AWS preferred) to build sca
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