Data Engineer

Swiggy

India

On-site

INR 800,000 - 1,200,000

Full time

14 days+

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Job summary

A leading food delivery platform in India is seeking a Data Analyst with 2–4 years of experience to collaborate with the Data Engineering team and optimize data processes. Responsibilities include managing data pipelines, executing performance tuning, and working with large datasets. Ideal candidates will have a Bachelor's or Master's degree in a quantitative field and proficiency in SQL, R, Python, and tools like Snowflake and Spark. Join a dynamic team and leverage data-driven insights to solve real-world problems.

Qualifications

  • 2–4 years of analytics, data science, or related experience.
  • Hands‑on experience with Query Profiles and bottleneck identification.
  • Proficient verbal and written communication skills.

Responsibilities

  • Partner closely with the Data Engineering team for data management.
  • Optimize data pipelines and queries for improved performance.
  • Contribute to the DataOps framework for automated data processes.

Skills

SQL
R
Python
Excel
Data Manipulation

Education

Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or related field

Tools

Snowflake
Spark
Databricks

Job description

Swiggy is India’s largest on-demand convenience platform, redefining the way people access food, groceries, and everyday essentials. Established in 2014, Swiggy operates across 500+ cities with a robust logistics network that ensures fast and reliable doorstep delivery. From restaurant meals to groceries via Instamart and hyperlocal pick-up and drop services through Genie, Swiggy has become an integral part of daily life for millions of Indians, combining technology, scale, and convenience in a seamless digital experience.

Job Roles & Responsibilities
Collaboration with Data Engineering Team
  • Partner closely with our Data Engineering team to ensure efficient data collection, storage, and processing
  • Collaborate in designing and optimizing data pipelines for seamless data movement
  • Work jointly on data architecture decisions to enhance analytics capabilities
Performance Tuning and Query Optimization
  • Dive into large, complex datasets to create efficient and optimized queries for analysis
  • Identify bottlenecks and optimize data processing pipelines for improved performance
  • Implement best practices for query optimization, ensuring swift data retrieval
  • Contribute to the DataOps framework, automating data processes and enhancing data quality
  • Implement monitoring and alerting systems to ensure smooth data operations
  • Collaborate with the team to develop self-serve platforms for recurring analysis
  • Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or a related quantitative field
  • 2–4 years of analytics, data science, or related experience
  • Proficiency (2–4 years) in SQL, R, Python, Excel, etc., for effective data manipulation
  • Hands‑on experience with Snowflake and Spark/Databricks, adept at Query Profiles and bottleneck identification
  • Apply creative thinking to solve real‑world problems using data-driven insights
  • Embrace a "fail fast, learn faster" approach in a dynamic, fast-paced environment
  • Exhibit proficient verbal and written communication skills
  • Thrive in an unstructured environment, demonstrating attention to detail and self-direction
  • Foster collaboration and partnerships across functions
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