Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud-native data technologies, focusing on Microsoft Fabric/One Lake platforms.
Develop and optimize ETL/ELT workflows and implement data modeling to support analytics, reporting, dashboards, and machine learning workloads.
Ensure data quality, reliability, and operational excellence by monitoring, troubleshooting, performance tuning, and collaborating cross-functionally for data security and governance.
Minimum Requirements
Strong experience as a Data Engineer building and operating production data pipelines.
Hands-on experience with Apache Spark, Python, SQL, and cloud-based data platforms (Data Lakes, Lakehouse architectures).
Familiarity with Microsoft Fabric or One Lake is a strong plus.
Work Experience Required: 4+ years in data engineering or equivalent role (preferred).
Ideal Candidate Profile
Experienced in building and optimizing data pipelines in modern cloud environments, especially with batch and streaming data use cases.
Skilled in collaborative work with analytics engineers, data scientists, and platform teams for delivering trusted, analytics-ready datasets.
Comfortable with implementing CI/CD, schema management, and operational monitoring to drive efficiency and reliability in data engineering workflows.