Responsibilities:
About the role:
As a Junior/Senior Data Engineer, you'll be taking the lead in designing and maintaining complex data ecosystems. Your experience will be instrumental in optimizing data processes, ensuring data quality, and driving data-driven decision-making within the organization.
Architecting and designing complex data systems and pipelines. Leading and mentoring junior data engineers and team members. Collaborating with cross-functional teams to define data requirements. Implementing advanced data quality checks and ensuring data integrity. Optimizing data processes for efficiency and scalability. Overseeing data security and compliance measures. Evaluating and recommending new technologies to enhance data infrastructure. Providing technical expertise and guidance for critical data projects.
Required skills & experience:
Proficiency in designing and building complex data pipelines and data processing systems. Leadership and mentorship capabilities to guide junior data engineers and foster skill development. Strong expertise in data modeling and database design for optimal performance. Skill in optimizing data processes and infrastructure for efficiency, scalability, and cost-effectiveness. Knowledge of data governance principles, ensuring data quality, security, and compliance. Familiarity with big data technologies like Hadoop, Spark, or NoSQL. Expertise in implementing robust data security measures and access controls. Effective communication and collaboration skills for cross-functional teamwork and defining data requirements.
Preferred skill sets:
- Cloud: Azure/GCP/AWS
- DE Technologies: ADF, Big Query, AWS Glue etc.
- Data Lake & Data Warehouse : Snowflake, Data Bricks , AWS Redshift etc.
Education qualification:
BE/BTECH, ME/MTECH,MCA
Optional Skills
Accepting Feedback, Active Listening, Analytical Thinking, Artificial Intelligence, Big Data, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data-Driven Decision Making (DIDM), Data Engineering, Data Lake, Data Mining, Data Modeling, Data Pipeline, Data Quality, Data Science, Data Science Algorithms, Data Science Troubleshooting, Data Science Workflows, Deep Learning, Embracing Change, Emotional Regulation
