Senior Data Engineer (Elasticsearch/SQL)

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role: SeniorData Engineer - (SQL/Elasticsearch)

Experience : 3 - 8 Years

Work location: Mumbai, Bangalore & Trivandrum

Role & Responsibilities:

• Design and optimize search and analytics solutions using Elasticsearch for handling structured, semi-structured, and unstructured healthcare data.

• Build and optimize SQL-based ETL/ELT pipelines for ingestion, transformation, and reporting at scale.

• Diagnose and troubleshoot distributed systems problems, including search performance, query optimization, and data indexing challenges.

• Design and implement scalable storage and query solutions leveraging relational databases and search engines.

• Help developers in debugging data related issues.

• Capable of creating APIs using Python(fastAPI).

• Communicate effectively with Infrastructure, Network, DevOps, SiteOps, and customer teams to ensure smooth operations.

• Build automation and monitoring tools to ensure high availability and performance of SQL and Elasticsearch-based systems.

Must Have Skills:

• Strong expertise in SQL (query optimization, stored procedures, indexing, partitioning).

• Hands-on experience with Elasticsearch: designing indices, mapping, analyzers, query DSL, performance tuning, scaling clusters.

• Solid understanding of data modeling, normalization, and search schema design.

• Proficiency in Python for scripting and API development.

• Familiarity with GitHub/Bitbucket/GitLab for version control.

• Strong grasp of data structures, exception handling, and debugging.

• Experience with GCP services (BigQuery, Data Fusion, Pub/Sub, Cloud Storage) or equivalent AWS/Azure data services.

• Exposure to orchestration frameworks such as Airflow, NiFi, or Google Cloud Composer.

• Experience developing pipelines and utilities for data migration, storage, search, and analytics on Google Cloud.

• Experience in developing and maintaining large-scale data ingestion pipelines capable of handling terabytes of daily data.

• Familiarity with message/event streaming solutions such as Kafka, Kinesis, or Pub/Sub.

• Knowledge of containerization and orchestration (Docker, Kubernetes).

• Hands-on experience in optimizing Elasticsearch clusters for high availability, security, and scalability in production.

• Experience supporting large-scale, real-time data systems in production.