Data Engineer

Expected to be an SME.
Collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute to key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Design and develop highly scalable data pipelines and ETL/ELT processes for large-scale data processing.
Build and maintain data services/APIs for seamless data consumption across systems.
Ensure data quality, validation, and consistency across pipelines.
Optimize data workflows for scalability, performance, and cost efficiency.
Handle high-volume and high-velocity datasets with efficient processing strategies.
Mentor junior team members to foster their professional growth and development.
Continuously evaluate and improve data engineering processes to enhance team productivity.

Professional & Technical Skills:
Must To Have Skills: Proficiency in Python (Programming Language).
Strong experience in building scalable data pipelines and distributed data processing systems.
Solid understanding of databases (SQL and NoSQL) and advanced query optimization techniques.
Experience with ETL/ELT frameworks and data integration patterns.
Hands-on experience with multi-cloud platforms (AWS, Azure, or Google Cloud) and cloud-native data services.
Experience with workflow orchestration tools (e.g., Apache Airflow or equivalent).
Familiarity with CI/CD tools (Git, Jenkins) and containerization (Docker).
Strong understanding of performance tuning, scalability, and distributed system design principles.
Understanding of data quality, data lineage, and governance frameworks.
Good To Have Skills: Exposure to programming languages such as Java or Scala in distributed environments.

Additional Information:
The candidate should have a minimum of 5 years of experience in Python (Programming Language).
A 15 years full-time education is required.