Data Engineer/Architect – EDGE|ML

Description

EDGE|ML is an end-to-end analytics and solutions platform aiming to supply SCM, logistics, store and category managers with data, insights, and solutions to optimize their processes. EDGE|ML is built on a state-of-the-art, scalable technology leveraging Google Cloud Platform managed services.

The ideal candidate for the Data engineer/architect role is an experienced data pipeline/architecture builder who enjoys building from the ground up and optimizing data systems.

Your challenges

- Augment EDGE|ML offerings by enhancing, extending, optimizing, and operationalizing the analytic services.

- Data Architecture

- Optimally design and work with large, complex datasets in BigQuery.

- Data Engineering

- Design, build, maintain, productionize, and operate data pipelines in GCP using Python, SQL, and Google managed services.

- Deploy machine learning models.

- Collaborate closely with business stakeholders, data analysts/scientists, software engineers, and platform operations staff.

You should bring in

- Data architecture

- 5+ years of experience in Data Warehousing, Business Intelligence, Big Data.

- Advanced working SQL knowledge and experience (CTE, window functions) working with relational databases, as well as working familiarity with a variety of databases.

- Extensive knowledge of data modelling approaches and best practices.

Experience in implementation of a data mesh architecture in Google Cloud is a solid plus.





- Extensive knowledge of techniques for query optimization in BigQuery.

- Data Engineering

- 5+ years of experience in a Data Engineering role

- Extensive experience building, optimizing, and productionizing ‘big data’ data pipelines, in Google Cloud Platform.

- Experience designing and deploying high performance systems with reliable monitoring and logging practices.

- Experience with source control systems (GitHub) and continuous integration & deployment tools e.g. Jenkins

- Experience using application containerization technologies (Docker, Kubernetes), orchestration and scheduling (e.g.

Google

Composer, Apache Airflow)

- Experience with machine learning using packages such as xgboost, sklearn, TensorFlow (building, deploying, monitoring)

- Experience building data pipelines for Gen AI product Knowledge of professional software engineering practices, craftsmanship of clean and efficient code

- Intense curiosity and tenacity in staying ahead of with technology and continually striving to be better at your craft.

- Strong interpersonal skills, comfortable in communicating with users, other technical teams, and business stakeholders to understand requirements, describe data modeling and data engineering decisions.

- Ability to contribute to an open, international team culture to drive the knowledge exchange and learning of all team members. Fluency in English (both written and spoken) is a must-have.

📌 Data Engineer/Architect – EDGE|ML (Noida)
🏢 Topcoder
📍 Noida