Summary:

As a Data Engineer, you will work closely with Product Managers, Data Architects, Solution Architects, Business Analysts, and fellow engineers to design, build, test, and maintain cloud-native data solutions on Google Cloud Platform (GCP). You will play a key role in transforming enterprise data into trusted, high-quality data assets that drive business insights and operational excellence.

Responsibilities:

- Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform (GCP).
- Build and optimize data solutions using Dataproc, BigQuery, SQL, and dbt.
- Develop and maintain high-quality data models that support reporting, analytics, and AI use cases.
- Ingest, transform, validate, and publish data from multiple enterprise source systems.
- Collaborate with Product Managers, Business Analysts, Data Architects, and engineering teams to understand business requirements and deliver scalable data solutions.
- Develop reusable data transformation components and adhere to established engineering standards and best practices.
- Optimize data processing performance, reliability, and cost efficiency.
- Perform unit testing, data validation, and production support to ensure data quality and operational stability.
- Participate in Agile ceremonies, including sprint planning, backlog refinement, and code reviews.
- Document technical designs, data flows, and implementation details.

Required Qualifications:

- Bachelor’s degree in Computer Science, Engineering,



Information Systems, or a related field, or equivalent practical experience.
- 4+ years of experience in Data Engineering.
- Hands-on experience developing data solutions on Google Cloud Platform (GCP).

- Solid experience with

- Dataproc

- BigQuery
- SQL
- dbt (Data Build Tool)
- Strong knowledge of data modeling techniques, including dimensional modeling and analytical data warehouse concepts.
- Experience building scalable ETL/ELT pipelines and processing large datasets.
- Familiarity with software development best practices, including Git-based version control and CI/CD.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.

Preferred Qualifications:

- Experience with Apache Airflow for workflow orchestration.
- Experience integrating with Apache Kafka or other event streaming platforms.
- Working knowledge of PySpark for distributed data processing.
- Experience using Python for data engineering, scripting, and automation.
- Knowledge of data quality, metadata management, and data governance principles.
- Domain Experience (Highly Desirable)
- Experience in one or more of the following domains is highly desirable:
- Retail industry (Apparel)
- Supply Chain data platforms
- Transportation and Logistics
- Warehouse Management Systems (WMS)
- Distribution Center operations

#AditiConsulting # 26-04751

📌 Data Engineer (Bengaluru)
🏢 Aditi Consulting
📍 Bengaluru