Job Title : Data Engineer

Experience : 6- 9 Years

Summary :

We are seeking an experienced Data Engineer with 6- 9 years of expertise in designing, developing, and optimizing large-scale data platforms and pipelines. The ideal candidate should have strong hands-on experience in Python, PySpark, Snowflake, ETL development, and Big Data Architecture, with the ability to build scalable and high-performance data solutions that support analytics and business intelligence initiatives.

Roles & Responsibilities :

- Design, develop, and maintain scalable data pipelines for batch and real-time data processing.

- Architect and implement robust Big Data solutions to support enterprise-wide analytics and reporting needs.

- Build and optimize ETL/ELT workflows using Python, PySpark, and modern data engineering frameworks.

- Develop and manage data models, data warehouses, and data marts within Snowflake environments.

- Collaborate with data analysts, data scientists, and business stakeholders to understand and translate data requirements into technical solutions.

- Ensure data quality, integrity, governance, and security across multiple data sources and platforms.

- Optimize data processing jobs, query performance, and storage utilization to improve efficiency and reduce costs.

- Monitor, troubleshoot, and resolve issues related to data ingestion, transformation, and pipeline performance.

- Implement best practices for CI/CD, code reviews, testing, documentation, and deployment of data engineering solutions.

- Stay current with emerging technologies and recommend improvements to enhance the organization's data architecture and engineering capabilities.

Requirements :

- 6- 9 years of experience in Data Engineering, Data Warehousing, or Big Data technologies.

- Strong programming skills in Python with experience in developing scalable data processing applications.

- Hands-on expertise in PySpark for distributed data processing and transformation.

- Proven experience designing and implementing Big Data architectures and data lake solutions.

- Strong experience with Snowflake, including data modeling, performance tuning, and warehouse optimization.

- Extensive experience building and maintaining ETL/ELT pipelines for large-scale data environments.

- Good understanding of data warehousing concepts, dimensional modeling, and database design principles.

- Experience working with cloud platforms such as AWS, Azure, or GCP is preferred.

- Familiarity with orchestration and workflow tools such as Airflow, Azure Data Factory, or similar platforms.

- Strong analytical, problem-solving, communication, and stakeholder management skills with the ability to work in an Agile environment.

Preferred Qualifications :

- Experience with streaming technologies such as Kafka or Spark Streaming.

- Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation.

- Exposure to data governance, metadata management, and data quality frameworks.

- Relevant cloud or Snowflake certifications are a plus.