Meesho is hiring Software Development Engineer III โ Data professionals in Bangalore, a role positioned as equivalent to SDE-II according to the hiring information provided. This opportunity is ideal for engineers who enjoy working with large-scale data platforms, distributed systems, streaming technologies and high-performance data processing.
๐ Location: Bangalore, Karnataka
๐ผ Role: Software Development Engineer III โ Data / SDE-II Data
๐งโ๐ป Experience mentioned: 2โ4 Years
๐ ๏ธ Core Area: Big Data & Data Engineering
โก Key Technologies: Kafka, Spark, Delta Lake, Presto, Airflow, Flink, AWS
๐ข About Meesho
Meesho is one of India’s leading internet commerce companies, focused on democratizing e-commerce and enabling small businesses and entrepreneurs to reach customers across India. Its technology platform operates at significant scale, supporting millions of orders and a large, diverse user base.
For data engineers, this environment creates opportunities to work on systems where data availability, processing speed, reliability and scalability directly influence business decisions and customer experiences.
๐ผ Why Is This Role Good for Your Experience?
You can gain practical exposure to:
๐น Apache Kafka and real-time data streaming
๐น Apache Spark and Spark performance tuning
๐น Delta Lake and modern data-lake architectures
๐น Presto/Trino-style distributed SQL processing
๐น Apache Airflow orchestration
๐น Apache Flink/Spark Streaming
๐น AWS Big Data services
๐น Data modeling and pipeline architecture
๐น Large-scale performance optimization
๐น Data engineering for e-commerce workloads
This experience can position you for future roles such as Senior Data Engineer, Data Platform Engineer, Big Data Engineer, Distributed Systems Engineer or Data Engineering Lead.
๐ ๏ธ Skills Required
Core Big Data
- Apache Spark
- Kafka
- Hive / Impala
- Delta Lake
- Presto / Trino
- Airflow
- Apache Flink / Spark Streaming
Programming
- Java
- Scala
- Python
- Advanced SQL
Cloud
- AWS Big Data services
- S3
- EMR
- Cloud-based data processing
Data Engineering
- ETL/ELT
- Data modeling
- Data pipelines
- Batch and streaming architecture
- Data quality
- Partitioning and optimization
๐ฏ Preparation Tips
1๏ธโฃ Go Deep Into Spark
Don’t stop at knowing how to write a Spark job.
Prepare Spark execution, partitions, shuffle, joins, caching, Catalyst optimizer, Tungsten, broadcast joins and memory management.
2๏ธโฃ Prepare Kafka Architecture
Understand:
- Topics
- Partitions
- Consumer groups
- Offsets
- Replication
- Ordering
- Delivery semantics
- Retention
- Rebalancing
3๏ธโฃ Master SQL
Prepare complex SQL involving:
- Window functions
- CTEs
- Ranking
- Aggregations
- Joins
- Deduplication
- Slowly changing data
- Performance optimization
4๏ธโฃ Understand Batch vs Streaming
Be ready to compare Spark batch, Spark Streaming and Flink and explain when you would choose one over another.
5๏ธโฃ Think in Terabytes
The strongest preparation strategy for this JD is to practice designing systems around large data volumes, not small datasets.
For example:
โDesign a real-time analytics pipeline for millions of e-commerce events per hour.โ
Discuss ingestion โ Kafka โ processing โ storage โ serving โ monitoring.
๐ค Expected Meesho Interview Rounds
One documented SDE-2 Data Engineer interview experience included an initial HackerRank assessment covering SQL, DSA and algorithms, followed by a technical coding/DSA interview and additional technical discussions.
A practical preparation structure would therefore be:
Round 1 โ Online Assessment
SQL + DSA + programming.
Round 2 โ Coding/DSA Interview
Medium-to-hard coding problems and problem-solving.
Round 3 โ Data Engineering Technical Round
Kafka, Spark, Airflow, streaming, SQL and pipeline architecture.
Round 4 โ Data/System Design
Design a scalable batch/streaming platform and discuss reliability, performance and cost.
Round 5 โ Managerial/Bar-Raiser Discussion
Ownership, architecture decisions, collaboration and handling ambiguous engineering problems.
๐ฐ Salary Range
Current employee-reported Glassdoor data for Meesho SDE-II shows an average base salary of approximately โน31 lakh/year, with reported base compensation around โน28โ36 lakh/year and average additional pay of about โน8 lakh/year.
๐ฐ โน28โ45+ LPA total compensation
๐ Resume Tips for This JD
Avoid a generic โData Engineerโ resume.
Your headline should immediately communicate your specialization:
Data Engineer | Apache Spark | Kafka | AWS | Delta Lake | Airflow | Big Data
Quantify scale wherever possible.
Instead of:
โ โWorked on Spark pipelines.โ
Write:
โ โDesigned and optimized Spark pipelines processing 5+ TB of daily data, reducing processing time by 35% through partitioning and join optimization.โ
Highlight:
๐ Data volume
๐ Pipeline latency
๐ Cost optimization
๐ Kafka throughput
๐ Spark performance improvements
๐ Batch/streaming architecture
๐ AWS services
๐ Data quality improvements
๐ฉ How to Apply
๐ Application Link: Click Here
Candidates interested in the opportunity should apply through the official Meesho careers portal and search for Software Development Engineer III โ Data in Bangalore.
Before applying, verify the current experience requirement because the active official listing currently shows 5โ8 years, which differs from the 2โ4 years mentioned in the hiring post provided here.
๐ Final Takeaway
The Meesho SDE-III/SDE-II Data opportunity is an excellent target for engineers who want to build expertise in large-scale distributed data systems.
If you enjoy solving problems involving Kafka, Spark, streaming, data lakes, SQL and cloud infrastructure, this role can provide strong exposure to the engineering challenges behind a high-scale e-commerce platform.
That combination of coding + Big Data + system design + performance engineering is what can make your profile stand out for Meesho’s Data Engineering teams. ๐
