Job Title: Senior Data Engineer
Experience: 6 - 8 years
Location: Hybrid
Employment Type: Full-time
Mandatory skills: AWS, Python, SQL, Databricks
About The Role
We are looking for a highly skilled
Senior Data Engineer who is passionate about building robust, scalable, and high-performance data systems. The ideal candidate will have deep expertise in
SQL, Python, AWS, and Databricks, with a proven track record of designing and implementing modern data pipelines and analytical frameworks.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes for data ingestion, transformation, and storage.
- Work with cross-functional teams to define and deliver data solutions supporting business and analytics needs.
- Optimize and fine-tune SQL queries, data models, and pipeline performance.
- Build and manage data workflows in Databricks and integrate with AWS data services (S3, Redshift, Glue, Lambda, etc.).
- Ensure data accuracy, consistency, and reliability through data quality checks and monitoring frameworks.
- Collaborate with Data Scientists, Analysts, and Product teams to enable self-service analytics and advanced data-driven insights.
- Follow best practices for data governance, security, and compliance.
- Continuously evaluate emerging data technologies and propose innovative solutions for process improvement.
Required Skills & Qualifications
- Bachelor's or master's degree in computer science, Information Technology, or a related field.
- 5+ years of hands-on experience in Data Engineering or related roles.
- Strong proficiency in SQL for complex query development and data manipulation.
- Expertise in Python for building data processing and automation scripts.
- Experience with AWS ecosystem especially S3, Glue, Redshift, Lambda, and EMR.
- Hands-on experience with Databricks for data processing, transformation, and analytics.
- Experience working with structured and unstructured datasets in large-scale environments.
- Solid understanding of ETL frameworks, data modeling, and data warehousing concepts.
- Excellent problem-solving, debugging, and communication skills.
Good to Have
- Experience with Airflow, Snowflake, or Kafka.
- Knowledge of CI/CD pipelines and Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
- Exposure to data governance, metadata management, and data cataloguing tools.
Skills: python,databricks,sql,aws
