Senior Data Engineer

At Shaadi.com, we're not just building a platform — we're playing Cupid for millions across the world! Behind every successful match, swipe, and connection lies a continuous stream of data. With over 100+ million records generated daily, we rely on rock-solid data engineering to power real human stories, smart recommendations, and seamless user experiences.

If you love building heavy-duty pipelines, taming data lakes, and turning raw data streams into matchmaking magic, this is your sign to join our team!

What You'll Do (Your Daily Quests)

Build High-Volume Pipelines: Design, build and maintain scalable data pipelines (real-time and batch) and large-scale distributed systems that ingest, process and organize large volumes of data.

Architect Data Lakes & Warehouses: Manage scalable data architecture across AWS (S3, Redshift, Glue) so our Data Science, Product, and Analytics teams have clean, queryable data at their fingertips.

Stream in Real-Time: Work with streaming frameworks like Kafka to move event data instantly — making sure live activity, recommendations, and notifications happen without a hitch .

Data Zen & Quality Control: Clean, structure, and optimize raw datasets. Monitor data drift, system performance, and maintain immaculate data reliability .

Cross-Functional Collaboration: Partner with Product, Backend Engineering and Data Science teams to build features that directly impact business metrics and user happiness .

What You Bring (Your Tech Superpowers)

Coding Mastery: 2–4 years of hands-on experience in Python (Java or Go is a great plus!) with advanced SQL wizardry .

Cloud & Big Data: Solid experience with AWS services (Redshift, S3, Glue, CloudFormation, or ECS) and modern data lake setups.

Streaming & Messaging: Hands-on experience or deep understanding of the Kafka ecosystem (or AWS Kinesis).

ETL & Data Modeling: Proven track record of writing efficient, complex ETL/ELT jobs and understanding microservices architectures.

Dev Tools: Comfortable with Git version control, CI/CD pipelines, and writing optimized queries.

Bonus Points & Culture

Nice to Have: Familiarity with Elasticsearch, Snowplow, or Docker , and curiosity about how data feeds into ML models & recommender systems .

Real Human Impact: Your pipelines directly power products that help millions find their life partners.

Scale & Growth: Work on complex, high-velocity data problems that will rapidly elevate your engineering career.

Great Vibe: Collaborative teams, vibrant office culture, and brainstorming overchai!