Work Mode - Hybrid. Exp - 5+ Years. Interview Mode - Face to Face.

Roles & Responsibilities :

- Design and implement modern data architectures across cloud and hybrid environments.

- Develop and optimize data pipelines and ETL/ELT processes for high-volume, high-velocity data.

- Lead data platform modernization initiatives using cutting-edge tools and frameworks.

- Define and enforce data governance, security, and compliance standards.

- Partner with Data Science, BI, and Product teams to ensure data availability, accuracy, and performance.

- Provide technical leadership and mentorship to data engineers and developers.

- Implement DevOps/Data Ops practices for automated testing, deployment, and monitoring.

- Continuously evaluate and introduce innovative data technologies that enhance efficiency and scalability.

- Translate business requirements into robust and scalable technical data solutions.

- Support real-time and streaming data architectures for analytics and ML workloads.

- Designing and developing REST APIs / Azure App Services and implementing Azure PaaS solutions.

Required Skills & Qualifications :

- Bachelors or masters in computer science, Engineering, or related field.

- 8+ years in Data Engineering or Data Architecture roles.

- Expertise in Python, SQL, Spark, Kafka, and Airflow.

- Proven experience with cloud platforms (AWS, Azure, or GCP).

- Hands-on experience with Snowflake, Databricks, or Delta Lake.

- Strong understanding of data modelling, governance, and lineage tools.

- Excellent problem-solving, leadership, and communication skills.