Role Overview:

The Data Engineer will design, build, and maintain the data infrastructure that powers analytics and AI-driven features across the product. The role will combine solid engineering capabilities with hands-on ownership of data pipelines, warehouses, and integrations, working closely with engineering and business teams to build reliable, scalable data pipelines and ensure high-quality data is available for downstream systems.

Role & responsibilities:
Data Pipeline Engineering
Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Develop and maintain infrastructure for real-time and batch data processing.
Build and optimise data models and schemas to support reporting and experimentation.
Data Warehousing & Infrastructure
Architect and manage data warehouses, data lakes, and database systems for analytics and ML workloads.
Optimise query performance and manage cost/efficiency of data storage and compute.
Work with cloud platforms (AWS, GCP, or Azure) to build and maintain data infrastructure.
Data Quality & Governance
Implement data quality checks, monitoring, and alerting to ensure pipeline reliability and data integrity.
Apply data governance, security, and privacy best practices across systems.
Integration & Automation




Build and orchestrate ETL/ELT pipelines using tools such as Airflow, dbt, or equivalent.
Develop web and app data scraping/extraction solutions (BeautifulSoup, Scrapy, Selenium, or similar).
Integrate APIs and third-party data sources into the data ecosystem.
Support LLM/AI pipelines with data feeds or vector stores.
Cross-Functional Collaboration
Partner with engineering and business teams on real-world use cases such as event tracking, customer 360 pipelines, personalisation data feeds, and automation.
Translate business and product requirements into robust, scalable data infrastructure.
Continuous Improvement
Stay current with advancements in data engineering, cloud data platforms, and AI infrastructure.
Identify prospects to adopt streaming platforms, big data tools, and containerisation where relevant.

Preferred candidate profile
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
Hands-on experience building and maintaining production-grade ETL/ELT pipelines and data warehouses.
Experience with cloud data platforms (AWS, GCP, or Azure).

Exposure to supporting LLM/AI pipelines or automation use cases will be an added advantage.

📌 Data Engineer Mumbai
🏢 Fruveggie Technology
📍 Mumbai