About the Role :

We are looking for a highly skilled and experienced Senior Data Engineer to design, develop, and optimize scalable data platforms and pipelines that support business intelligence, analytics, reporting, and data-driven decision-making across the organization.

The ideal candidate should possess strong expertise in data engineering, cloud platforms, big data technologies, ETL/ELT development, and database optimization.

This role requires close collaboration with data analysts, data scientists, business teams, and engineering stakeholders to build reliable, high-performance, and scalable data solutions.

Key Responsibilities :

- Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.

- Build robust data ingestion frameworks from multiple internal and external data sources.

- Develop and optimize batch and real-time data processing systems.

- Ensure data quality, integrity, consistency, and availability across platforms.

- Automate data workflows and orchestration processes.

- Design and implement scalable data architectures and data lake/data warehouse solutions.

- Build and optimize enterprise-level data models and storage systems.

- Support cloud-based data engineering initiatives and platform modernization.

- Monitor system performance and optimize data processing efficiency.

- Implement best practices for data governance, security, and compliance.

Cloud & Big Data Technologies :

- AWS

- Azure

- Google Cloud Platform (GCP)

- Snowflake

- Support large-scale distributed data processing systems.

- Develop and optimize complex SQL queries, stored procedures, and transformations.

- Work with relational and NoSQL databases including :

a. PostgreSQL

b. MySQL

c. SQL Server

d. MongoDB

e. Cassandra

- Perform performance tuning, indexing, and query optimization.

- Collaborate with Data Scientists, BI teams, Product teams, and business stakeholders.

- Support reporting, dashboarding, and advanced analytics use cases.

- Enable self-service analytics through scalable and clean data models.

- Translate business requirements into scalable technical solutions.

- Implement CI/CD pipelines for data engineering workflows.

- Monitor and troubleshoot production data pipelines and workflows.

- Ensure high availability and reliability of data infrastructure.

- Build logging, monitoring, and alerting mechanisms for data systems.

Required Skills & Expertise :

Technical Skills :

Strong expertise in :

a. Python

b. SQL

c. Spark

d. ETL/ELT Development

e. Data Warehousing

f. Data Modeling

Hands-on experience with :

a. Airflow

b. Kafka

c. Hadoop

d. Databricks

e. Snowflake

- Strong understanding of distributed data processing and scalable architectures