Data Engineer : SQL, Snowflake, Python

Talent Worx is seeking an experienced Data Engineer with expertise in SQL, Snowflake, and Python to enhance our data processing capabilities. In this role, you will be responsible for building and optimizing data pipelines, ensuring data quality, and supporting analytics initiatives. The ideal candidate will possess a strong technical background and a passion for transforming data into actionable insights.

• Experience: 5 to 8 years
• Location: Any where in india

Requirements

Key Responsibilities:

1. Develop and maintain scalable data pipelines to ingest, process, and store data using Snowflake.

2. Write efficient SQL queries for data extraction, transformation, and loading (ETL).

3. Utilize Python for data manipulation, data quality checks, and automation of data processes.

4. Collaborate with data scientists and analysts to define data requirements and deliver high-quality datasets.

5. Monitor and troubleshoot data pipeline performance and improve processes based on findings.

6. Ensure data integrity and quality through rigorous validation and testing methodologies.

7. Document data processes, architecture, and any technical specifications.

8. Stay updated with emerging technologies and industry best practices.

Technical Skills:

- Proficiency in SQL and experience with Snowflake for data warehousing solutions.

- Strong command of Python for data processing and engineering tasks.

- Familiarity with ETL tools and data integration practices.

- Understanding of data modeling, data architecture, and data governance.

- Experience with cloud platforms (e.g., AWS, Azure) is a plus.

Required Qualifications:

1. Bachelor’s degree in Computer Science, Engineering, or a related field.

2. 4 to 8 years of experience in data engineering or a related field.

3. Solid understanding of data warehousing concepts and technologies.

4. Excellent problem-solving skills and attention to detail.

5. Strong communication skills and ability to work collaboratively in a remote team.