Description :

About the Team :

The Data-Tech team operates like an R&D division focused on solving business challenges through automation and scalable systems. The team comprises ecopreneurs who work across roles Business Analyst, Data Scientist, and Data Engineer to build robust, research-driven solutions using the latest tools and technologies.

Key Responsibilities :

Data Engineering & Pipeline Development :

- Design, build, and maintain resilient and scalable data pipeline architectures.

- Develop infrastructure for optimal data extraction, transformation, and loading (ETL) from diverse data sources.

- Work extensively with Advanced SQL, Python, and other modern technologies for data cleaning, wrangling, and transformation.

Analytics Support & Business Insights :

- Model datasets and collaborate with business leaders to answer key business questions.

- Build dashboards to enable data-driven decision-making.

- Own the design, development, and maintenance of new and ongoing projects, metrics, and analyses.

Cross-Functional Collaboration :

- Partner with cross-functional teams to ensure data cleanliness, accuracy, and completeness.

- Work closely with analytics and data science teams to help productionize ML models and other production-grade code.

Problem Solving & Research :

- Approach problem statements from first principles to uncover insights and propose solutions.

- Participate in research-oriented projects with an aim to publish research papers or technical content.

Required Qualifications & Skills :

Education :

- B.E./B.Tech in Computer Science/Engineering (Tier-I college candidates preferred).

Technical Skills :

- 13 years of experience in Data Engineering.

- Strong command of Python (pandas, numpy, scipy, matplotlib, data wrangling libraries).

- Expertise in Advanced SQL, performance tuning, and optimization.

- Experience with shell scripting and Git.

- Working knowledge of Airflow for orchestration.

- Understanding of Data Warehouse concepts.

Database Expertise :

RDBMS :

- PostgreSQL (preferred), MySQL, MS SQL Server

NoSQL :

- Elasticsearch (preferred), MongoDB, Cassandra

Data Warehouses :

- Amazon Redshift (preferred), BigQuery

Other storages :

- Firebase, GCS, S3

- Knowledge of Redshift administration is a plus.

Cloud & DevOps :

- Experience with AWS or other cloud platforms.

- Exposure to DevOps/ML-Ops is an added advantage.

Domain Knowledge :

- Knowledge of the FMCG Industry is a bonus.