As a Data Engineer you will design develop and maintain data solutions for data generation collection and processing.
Your typical day will involve creating data pipelines ensuring data quality and implementing ETL processes to migrate and deploy data across systems. You will play a crucial role in managing and optimizing data infrastructure to support the organizations data needs.
Roles & Responsibilities: Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to workrelated problems.
Design and develop data pipelines to extract transform and load data across systems.
Ensure data quality and integrity by implementing data validation and cleansing processes.
Collaborate with crossfunctional teams to understand data requirements and design efficient data solutions.
Optimize and maintain data infrastructure to support data processing and analysis.
Troubleshoot and resolve datarelated issues and performance bottlenecks.
Stay updated with the latest industry trends and technologies in data engineering.
Provide guidance and mentorship to junior data engineers.
Professional & Technical Skills: Must To Have Skills: Proficiency in Python (Programming Language)
Strong understanding of data engineering concepts and best practices.
Experience with data modeling database design and SQL.
Handson experience with ETL tools and frameworks such as Apache Spark or Apache Airflow.
Familiarity with cloud platforms such as AWS or Azure for data storage and processing.
Knowledge of big data technologies like Hadoop Hive or Kafka.
Experience with version control systems like Git for code management.
Excellent problemsolving and analytical skills.
Additional Information: The candidate should have a minimum of 3 years of experience in Data Engineering