Senior Data Engineer
About the role
The Senior Data Engineer will lead the architecture, design, and deployment of enterprise data infrastructure. Responsibilities include ownership of complex data pipelines, architectural decisions, and ensuring scalable, secure, and production-ready data ecosystems. The role bridges data engineering, backend services, and machine learning operations (MLOps), with duties spanning pipeline architecture, big data ecosystem management, backend/API integration, orchestration, DevOps, MLOps infrastructure, and mentorship of junior engineers. The position requires hands-on experience, technical leadership, and proficiency in modern data engineering tools and practices.
Must have
- Experience: Minimum 5+ years of hands-on experience in Data Engineering.
- Lead the small team and guide junior engineers.
- Best Practices need to follow on production ready setup.
- Efficient code design pattern usage.
- Multithreading knowledge.
- Expertise in git end point version handling.
- Heavily hands on experience expecting.
- Programming: Strong proficiency in Python. Solid experience with backend frameworks like FastAPI and Spring Boot.
- Big Data & Streaming: Extensive experience with Hadoop environments, Apache Spark, Kafka, and Airflow are must requirements.
- ETL/Orchestration: Deep expertise in ETL pipeline creation, productionizing data workflows, Airflow, and dbt Databases: Advanced SQL skills with deep knowledge of DB2 SQL and PostgreSQL. Capable of handling massive time-series datasets. Work experience in IBM AS400 is advantageous.
- Infrastructure & Security: Proficiency with Linux CLI, Docker, Kubernetes, network configuration, and OAuth2 implementation.
- Exposure to Google Cloud Platform (GCP) services and architecture (or any other vendor).
Nice to have
- Having Banking domain experience is advantageous.
Technologies
- Airflow
- AS/400
- CLI
- Data Engineering
- Db2
- dbt
- DevOps
- Docker
- ELT
- ETL
- FastAPI
- GCP
- Git
- Hadoop
- Kafka
- Kubernetes
- Linux
- MLOps
- Model Deployment
- Multithreading
- NiFi
- OAuth
- PostgreSQL
- Python
- Spark
- Spring / Spring Boot
- SQL
- Time Series
Highlights
Application is via email to careers@orysys.com. The role expects hands-on experience and technical leadership, and offers opportunities for mentorship and working with advanced data and cloud technologies.
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