As a **Data Engineer** supporting **Law data strategy** , you will design, build, and maintain scalable data pipelines that integrate data from legal systems into Amgen's **enterprise data fabric** . You will enable high-quality, governed datasets that support **analytics, reporting, and emerging AI/ML use cases** for Legal and Compliance teams. This role requires strong hands-on engineering skills, familiarity with modern data platforms (e.g., Databricks), and the ability to work closely with Legal stakeholders, Data Architects, and AI/Analytics teams. **Key Responsibilities** **Data Engineering & Pipeline Development** + Design, develop, and maintain data pipelines to ingest data from **legal systems, third-party tools, and enterprise platforms** + Build and optimize **ETL/ELT pipelines** using modern frameworks (Databricks, Spark) + Implement reliable, scalable, and production-ready data pipelines using engineering best practices, monitoring, and automated validation frameworks + Integrate structured and unstructured legal data into the **enterprise data fabric** + Ensure reliability, scalability, and performance of data pipelines **Databricks & Modern Data Platform** + Develop pipelines using **Databricks (Delta Lake, Spark, notebooks)** + Implement data transformation and orchestration workflows + Support migration and modernization of legacy data solutions to cloud-native platforms + Contribute to reusable data engineering patterns and components + Optimize Delta Lake and Spark workloads for scalable, cost-productive, and high-performance enterprise data processing **Data Quality, Governance & Compliance** + Implement data quality checks,



validation rules, and monitoring + Implement governance, lineage, and security controls for sensitive legal and compliance datasets + Ensure compliance with **data governance, privacy, and legal/regulatory requirements** (e.g., sensitive legal data handling) + Maintain metadata, lineage, and documentation for legal datasets **AI & Advanced Analytics Enablement** + Build curated datasets that support **AI/ML models and GenAI use cases** + Prepare structured and unstructured datasets for AI/ML and GenAI use cases including document intelligence and semantic search applications + Enable feature engineering and data preparation for AI applications in Legal (e.g., document analysis, contract insights) + Collaborate with data scientists and AI teams to ensure data readiness and accessibility **Collaboration & Delivery** + Work with Legal stakeholders to understand data needs and translate into technical solutions + Partner with Data Architects to align with enterprise data fabric strategy + Participate in Agile development processes (sprint planning, estimation, delivery) + Document pipelines, models, and technical decisions **Basic Qualifications** + Master's or Bachelor's degree in Computer Science, Engineering, Information Systems,



or related field + **5-8 years** of experience in data engineering or related technical role **Must-Have Technical Skills** + Strong experience with **SQL** and relational databases + Programming experience in **Python (required), PySpark preferred** + Hands-on experience with **Databricks / Apache Spark** + Experience building **ETL/ELT pipelines** for large-scale datasets + Familiarity with **cloud platforms (AWS, Azure, or GCP)** + Understanding of **data modeling and data warehousing concepts** **Preferred / Strategic Skills (Aligned to Future Data Strategy)** + Certification: + Relevant certifications in Databricks, cloud platforms (AWS/Azure/GCP), or modern data engineering technologies are a plus + Experience with: + **Delta Lake / Lakehouse architectures** + **Data Fabric / Data Mesh concepts** + **Snowflake, Redshift, or enterprise data warehouse platforms** + Familiarity with: + **Streaming data (Kafka, event-driven pipelines)** + **Data orchestration tools (Airflow, Databricks Workflows)** + Exposure to: + **AI/ML data pipelines and feature engineering** + **Unstructured data processing (documents, legal text)** + Understanding of: + **Data governance frameworks and cataloging tools** + **Security and privacy controls for sensitive data (legal/compliance)** **Functional Skills** + Strong problem-solving and analytical thinking + Ability to work with large, complex datasets + Effective communication with both technical and non-technical stakeholders + Ability to operate in a fast-paced Agile environment

📌 Data Engineer (Hyderabad)
🏢 AMGEN
📍 Hyderabad