Data Engineer
Summary
Level 4 Data Engineer at Amgen's Hyderabad technology center: designs, builds, and maintains data pipelines and ETL/ELT solutions to deliver reliable, governed data for business decisions. Core stack is big data tooling — Databricks, Apache Spark/PySpark, SQL, AWS — plus growing exposure to AI solutions using LLMs, RAG, and AI-assisted dev tools.
Level 4 Data Engineer:
What you will do
Letsdo this.Letschange the world. In this vitalroleyou willbe responsible fordesigning, building,maintaining, analyzing, and interpreting data toprovideactionable insights that drive business decisions. This role involves working with large datasets, developing reports,supportingand performing data governanceinitiativesand,visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with database technologies, and a deep understanding of data architecture and ETL processes.
Roles Responsibilities:
- Design, develop, andmaintaindata solutions for data generation, collection, and processing
- Be a crucial team member thatassistsin design and development of the data pipeline
- Build 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
- Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.
- Take ownership of data pipeline projects frominceptionto deployment, manage scope, timelines, and risks
- Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
- Develop andmaintaindata 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 scalable and efficient data solutions
- Collaborate and communicate effectively with product teams
- 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
- Identifyand resolve complex data-related challenges
- Adhere to best practices for coding, testing, and designing reusable code/component
- Explore new tools and technologies that will help to improve ETL platform performance
- Participate in sprint planning meetings and provide estimations on technical implementation
What we expect of you
We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications:
- Masters/Bachelor'sdegree and 5 - 9 years of Computer Science,ITor related field experience
Preferred Qualifications:
Must-Have Skills:
- Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark,SparkSQL), workflow orchestration, performance tuning on big data processing
- Proficiencyin data analysis tools (eg.SQL) and experience with data visualization tools
- Excellent problem-solving skills and the ability to work with large, complex datasets
- Solid understanding of data governance frameworks, tools, and best practices.
- Knowledge of data protection regulations and compliance requirements
Good-to-Have Skills:
- Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
- Good understanding of data modeling, data warehousing, and data integration concepts
- Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
- Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.
Professional Certifications
- Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
Soft Skills:
- Excellent critical-thinking and problem-solving skills
- Good communicationand collaboration skills
- Demonstrated awareness of how to function in a team setting
- Demonstrated presentation skills