Manager_Data Engineer-- Data and Analytics_Advisory

• Architecting and designing complex data systems and pipelines.
• Leading and mentoring junior data engineers and team members.
• Collaborating with crossfunctional 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.

• 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 costeffectiveness.
• 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 crossfunctional teamwork and defining data requirements.

• Cloud Azure/GCP/AWS
• DE Technologies ADF, Big Query, AWS Glue etc.,
• Data Lake Snowflake, Data Bricks etc.,

Degrees/Field of Study required Master of Engineering, Bachelor of Engineering, Master of Business Administration Degrees/Field of Study preferred Microsoft Azure Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation