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).

Strong 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.

Solid 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