Data Engineer

ORYSYS Limitedtopjobs.lk

Oct 30, 2026, 7:35 PM3h ago

Colombo 3Data engineeringMid level (3+ yrs)

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About the role

The Data Engineer role at ORYSYS involves leading the architecture, design, and deployment of enterprise data infrastructure. The position bridges data engineering, backend services, and machine learning operations (MLOps). Key responsibilities include building scalable ETL/ELT pipelines, designing big data ecosystems, backend and API integration, workflow orchestration, DevOps, and supporting advanced data and MLOps practices. Candidates should have strong experience in Python, big data tools, ETL, databases, infrastructure, and MLOps.

Must have

Experience: Minimum 3+ years of hands-on experience in Data Engineering.
Programming: Strong proficiency in Python. Solid experience with backend frameworks like FastAPI and Spring Boot.
Big Data & Streaming: experience with Hadoop environments, Apache Spark, Kafka, and Airflow. These are must requirements.
ETL/Orchestration: Deep expertise in ETL pipeline creation, productionizing data workflows, Airflow, and dbt (not mandatory).
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.
MLOps: Proven knowledge and hands-on experience with MLOps principles and productionizing machine learning workflows.
Exposure to Google Cloud Platform (GCP) services and architecture. (or any other vendor).
Having Banking domain experience is advantageous.

Technologies

Airflow
AS/400
CLI
Data Engineering
Db2
dbt
DevOps
Docker
ELT
ETL
FastAPI
GCP
Hadoop
Kafka
Kubernetes
Linux
Machine Learning
MLOps
Model Deployment
NiFi
OAuth
PostgreSQL
Python
Spark
Spring / Spring Boot
SQL
Time Series

Highlights

Applications should be sent to careers@orysys.com. Experience with IBM AS400 and banking domain knowledge are considered advantageous. Exposure to Google Cloud Platform (GCP) or other cloud vendors is also beneficial.