About the Role:

We are looking for a skilled and experienced Senior Data Engineer to lead the design and implementation of scalable, high-performance data infrastructure. You will play a critical role in building robust ETL pipelines, architecting data models, and enabling real-time data processing systems across our platform. If you’re passionate about big data, cloud-native development, and engineering best practices, this role is for you.

Key Responsibilities

• Design, develop, and maintain high-performance ETL/ELT pipelines using Python, Apache Airflow, and DBT.

• Architect and optimize data models across relational (PostgreSQL), NoSQL (MongoDB), and cloud-based data warehouses like Redshift and Clickhouse.

• Build and maintain APIs for data access and integration using FastAPI.

• Lead real-time data processing and streaming solutions using Kafka or RabbitMQ.

• Design and implement scalable Spark-based data processing pipelines and caching solutions with Redis.

• Implement and manage search and analytics capabilities using Elasticsearch.

• Containerize and orchestrate data services using Docker and Kubernetes.

• Leverage AWS cloud services (S3, Lambda, Glue, ECS/EKS, RDS) to ensure secure and efficient data infrastructure.

• Establish and enforce data quality, governance, and security standards.

• Mentor junior data engineers and contribute to architectural decision-making and technical leadership.

 

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

• 4-6+ years of experience in data engineering, with a strong track record of building and scaling data infrastructure.

• Extensive experience with workflow orchestration tools like Apache Airflow.

• Deep expertise in relational (PostgreSQL) and NoSQL (MongoDB) database systems.

• Proficiency in designing data lakes and data warehouses with Clickhouse and Amazon Redshift.

• Practical experience with streaming frameworks such as Kafka or RabbitMQ.

• Solid hands-on experience with Spark, Redis, and Elasticsearch.

• Strong skills in containerization (Docker) and orchestration (Kubernetes).

• Cloud-native development experience using AWS services.

• Strong understanding of data modeling, data architecture, and performance optimization.

Preferred Skills:

• Experience with infrastructure as code (e.g., Terraform, CloudFormation).

• Knowledge of CI/CD pipelines and DevOps practices.

• Familiarity with data security, compliance (GDPR, HIPAA), and governance.

• Leadership experience in cross-functional teams or agile environments.

What We Offer:

• Free meals to all our employees over & above the CTC
• A collaborative, innovation-driven work culture
• Great learning curve
• Opportunities for leadership and technical mentorship
• Exposure to cutting-edge technologies and scalable product development
• Health benefits

Technical stack: Python, Fast API, Postgres SQL, Mongo DB, ETL pipelines, Docker, Kubernetes, Cloud (preferred AWS).

Expected Joining: Within a month.