India \- Hyderabad
JOB ID: R\-246943 LOCATION: India \- Hyderabad WORK LOCATION TYPE: On Site DATE POSTED: Jun. 12, 2026 CATEGORY: Information Systems
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.
- *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\-efficient, 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
- 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)**
- 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