Data Engineer
Applied Systems (company site, opens in a new tab)4+ yrsBengaluruOn-siteDirect career pageEst. 10–20 LPA
Posted on 2 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and operationalize scalable data pipelines with automated quality checks using GCP services and related technologies.
- Lead end-to-end pipeline development from data ingestion to consumption, optimizing ETL processes and ensuring high performance, availability, and scalability.
- Maintain and optimize data models and schemas for analytics, implement monitoring, troubleshooting, and uphold rigorous data quality standards.
Minimum Requirements
- 4+ years in Data/ETL Engineering with at least 1 year of Google Cloud Platform (GCP) development experience.
- Proven experience building and maintaining scalable Cloud Data Warehouses, preferably with Google BigQuery.
- Proficiency in SQL, Python, DBT, Apache Airflow, and ETL tools like Talend or Fivetran; familiarity with data modeling concepts like star and snowflake schemas.
- Bachelor’s degree in Computer Science, MIS, CIS, or equivalent; strong skills in Git for version control.
Ideal Candidate Profile
- Strong expertise in GCP data services (DataProc, Dataflow, BigQuery) and cloud-native data engineering best practices.
- Experienced in creating automated data quality checks and reusable components in ETL pipelines for efficient, scalable operations.
- Capable of designing data models and handling complex data integration using SQL, Python, and modern orchestration tools in a collaborative environment.