Senior Software Engineer – Data Engineering (3-5 Years Experience)

Myntra Data Platform (MDP) About The Role

- Myntra Data Platform (MDP) powers the data foundation behind analytics, experimentation, personalization, machine learning, and critical business decisions across Myntra.
- We are looking for a Senior Software Engineer – Data Engineering who is passionate about building scalable data platforms and production-grade data pipelines. You will work on large-scale batch and near real-time data processing systems, drive data quality and reliability, and contribute to the evolution of Myntra's modern lakehouse architecture.This role requires strong software engineering fundamentals combined with hands-on expertise in Apache Spark, SQL, Python, ETL development, workflow orchestration, data modeling, and up-to-date data platforms.You will collaborate with platform, analytics, product, and engineering teams to build highly reliable and scalable data solutions that power business-critical use cases across the organization.

What You'll Do

Data Pipeline Engineering

- Design, develop, and maintain scalable ETL/ELT pipelines for large-scale data processing.
- Build reliable data ingestion, transformation, validation, and publishing workflows.
- Develop reusable components and frameworks to improve engineering productivity.
- Implement incremental processing, backfills, retries, and failure recovery mechanisms.
- Ensure data pipelines meet reliability, scalability, and performance requirements.
- Apache Spark & Big Data Processing
- Build and optimize large-scale data processing jobs using Apache Spark, PySpark, and Spark SQL.
- Develop production-grade transformations, aggregations, and data enrichment pipelines.
- Analyze Spark execution plans and optimize jobs for performance and cost.
- Troubleshoot issues related to partitioning, joins, data skew, shuffles, and memory utilization.




- Follow engineering best practices for efficient distributed processing.
- Data Modeling & Warehousing
- Design and implement scalable data models for analytics and reporting.
- Build curated datasets supporting business intelligence and downstream applications.
- Apply dimensional modeling concepts including facts, dimensions, star schemas, and SCDs.
- Translate business requirements into reusable and maintainable data models.
- Workflow Orchestration
- Develop and manage workflows using Apache Airflow or equivalent orchestration platforms.
- Define task dependencies, scheduling strategies, retries, and monitoring mechanisms.
- Improve operational visibility and reliability of data workflows.
- Support self-service capabilities for pipeline onboarding and deployment.
- Lakehouse & Data Platform Engineering
- Build and operate workloads on Databricks and Spark-based platforms.
- Work with Delta Lake, Apache Iceberg, Parquet, or similar storage formats.
- Optimize storage layouts, partitioning strategies, compaction, and metadata management.
- Contribute to platform capabilities that simplify data consumption and processing.
- Data Quality & Governance
- Implement automated data quality validations and monitoring frameworks.
- Develop checks for freshness, completeness, schema validation, and consistency.
- Ensure proper metadata management, lineage tracking, and discoverability.
- Follow data governance and security best practices.
- Operational Excellence
- Monitor pipeline health, SLAs, performance, and cost metrics.




- Investigate production issues and perform root cause analysis.
- Improve platform stability through automation and continuous optimization.
- Participate in on-call support and incident management when required.
- Engineering Excellence
- Write clean, maintainable, and testable code.
- Participate in code reviews and design discussions.
- Contribute to engineering standards, best practices, and reusable frameworks.
- Collaborate with cross-functional teams to deliver high-quality solutions.

What We're Looking For

Required Qualifications

- 3-5 years of hands-on experience in Data Engineering or Software Engineering.
- Strong experience with Apache Spark, PySpark, and Spark SQL.
- Proficiency in Python and strong coding fundamentals.
- Excellent knowledge of SQL and query optimization techniques.
- Experience building production-grade ETL/ELT pipelines.
- Hands-on experience with Apache Airflow or similar workflow orchestration tools.
- Good understanding of data warehousing and data modeling concepts.
- Experience working with Databricks, Hadoop, or cloud-based data platforms.
- Familiarity with Delta Lake, Apache Iceberg, or Parquet.
- Strong debugging, troubleshooting, and problem-solving skills.
- Good understanding of software engineering best practices, CI/CD, and version control systems.

Preferred Qualifications

- Experience working with Kafka or other streaming technologies.
- Exposure to near real-time data processing architectures.
- Experience with dbt or similar SQL transformation frameworks.
- Knowledge of modern lakehouse architectures and cloud-native data platforms.
- Understanding of data governance, metadata management, and lineage concepts.
- Exposure to AI-assisted development tools and data engineering automation.
- Experience with Kubernetes, Docker, or cloud platforms such as GCP, AWS, or Azure

📌 Senior Software Engineer – Data Platform Engineering (Bengaluru)
🏢 Myntra
📍 Bengaluru