Data Engineer - Spark/Python (6-8 yrs)

Job Title : Data Engineer.

Location : Bangalore.

Experience Level : 6- 8 years.

Employment Type : Full-time with NAM INFO PVT LTD.

Shift timings : Rotational Shift (should be able to support 24 x 7).

Workdays : 5 days a week.

Job Description :

We are looking for experienced and talented Senior Data Engineers to join our team in Bangalore. As a Senior Data Engineer, you will be responsible for designing, developing, and optimizing data pipelines, working with both cloud platforms and modern data technologies. You will collaborate with cross-functional teams to ensure data solutions are efficient, scalable, and aligned with business requirements.

Key Responsibilities :

- Cloud Integration : Design and manage data solutions on AWS or Azure platforms, ensuring smooth integration with data systems.

- Data Warehousing : Develop and manage Data Warehouse solutions, ensuring data storage, transformation, and retrieval are efficient and scalable.

- Data Pipeline Development : Build and maintain ETL (Extract, Transform, Load) processes using modern ETL tools, with a focus on automation and scalability.

- Programming & Scripting : Write efficient and maintainable code using Python, Spark, and PySpark to process large datasets.

- Data Platform Management : Work with data platforms like Snowflake or Databricks to optimize data storage and processing, ensuring performance and cost-effectiveness.

- Database Management : Use any RDBMS (Relational Database Management System) to manage structured data, ensure data quality, and optimize database performance.

- SQL Expertise : Write complex SQL queries for data retrieval, analysis, and reporting, ensuring efficiency and accuracy.

- Collaboration : Work closely with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions that support decision-making.

Required Skills & Qualifications :

- 6 - 8 years of experience in data engineering or a similar role.

- Hands-on experience with cloud platforms such as AWS or Azure.

- Strong understanding of Data Warehousing concepts and architecture.

- Proficiency in Python, Spark, and PySpark for data processing and automation.

- Experience with Snowflake or Databricks for cloud-based data warehousing and analytics.

- Strong SQL skills and experience working with any RDBMS.

- Hands-on experience with any ETL tool to manage data pipelines.

- Familiarity with data integration, transformation, and migration strategies.

- Strong problem-solving skills and the ability to troubleshoot data-related issues.

- Excellent communication skills and the ability to work collaboratively with cross-functional teams.

Preferred Qualifications :

- Experience in working with large-scale data architectures and cloud data ecosystems.

- Familiarity with performance tuning and optimization techniques for ETL pipelines and databases.

- Certification in AWS or Azure.

- Experience with modern data tools and frameworks for real-time data processing.