
Senior Software Engineer
- Delhi Pune, Maharashtra
- Permanent
- Full-time
- Design and build scalable data pipelines using Dagster for orchestration and Snowflake for data warehousing
- Develop and optimize complex data models and transformations to support real-time analytics and AI/ML initiatives
- Build metadata-driven, reusable data solutions that enable self-service analytics across the organization
- Implement AI-powered data quality monitoring, anomaly detection, and automated data validation frameworks
- Partner with Data Scientists and ML Engineers to enable efficient model training and inference workflows
- Optimize query performance and cost efficiency across multi-petabyte data workloads in Snowflake
- Build robust data governance frameworks including lineage tracking, data cataloging, and access controls
- Implement event-driven data architectures supporting real-time customer experience optimization
- Collaborate with Product and Engineering teams to instrument applications for comprehensive data collection
- Mentor junior engineers on data engineering best practices and modern data stack technologies
- 4+ years of experience in data engineering roles with focus on large-scale data processing
- Expert-level proficiency in Python for data pipeline development and automation
- Strong hands-on experience with Snowflake including performance optimization, security, and cost management (must-have)
- Proven experience with Dagster or similar workflow orchestration tools (Airflow, Prefect)
- Deep understanding of data modeling, ETL/ELT patterns, and dimensional modeling techniques
- Experience with streaming data technologies (Kafka, Kinesis, Pub/Sub) and real-time processing
- Strong SQL skills with experience in query optimization and performance tuning
- Interest in AI/ML applications including feature engineering, model serving, and MLOps workflows
- Experience with cloud data platforms (AWS, GCP, Azure) and their native data services
- Knowledge of data governance tools and practices (data cataloging, lineage, quality monitoring)
- Familiarity with version control (Git) and CI/CD practices for data pipelines
- Experience with dbt for analytics engineering and data transformation
- Hands-on experience with vector databases and embedding pipelines for AI applications
- Knowledge of data mesh architecture and domain-driven data design
- Experience with Apache Spark for large-scale data processing
- Snowflake certifications (Data Engineer, Architect)
- Experience with customer data platforms (CDPs) and marketing analytics
- Understanding of privacy regulations (GDPR, CCPA) and data anonymization techniques