Data Engineer

Job Title AMDE110 - Data Engineer

Implementation partner:Altimetrik.

End client :Bank of New York Mellon Corporation (BNYM)

Office location: - Jersey city, (Onsite)

Duration C2C or fulltime

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Share resume to nainikarai@smsoftconsulting.com.

APPLY ONLINE

Skills required are :

MUST HAVE: Azure, Spark, Kubernetes

NICE TO HAVE: MongoDB and Pentaho

Job Description:

About Us:

We are a dynamic and innovative team at Altimetrik, serving as the implementation partner for the esteemed BNYM Bank of New York Mellon Corporation. As a Data Engineer, you will play a pivotal role in leveraging cutting-edge technologies to drive data-centric solutions.

Responsibilities:

Azure Cloud Expertise:

Harness the power of Azure cloud services to design, implement, and manage scalable data pipelines.

Ensure the secure and efficient storage, processing, and retrieval of data in the Azure environment.

Spark and Kubernetes Mastery:

Utilize Apache Spark for large-scale data processing, enabling real-time analytics and data transformations.

Implement and manage containerized applications using Kubernetes for seamless orchestration and scalability.

MongoDB Proficiency:

Leverage MongoDB for effective and efficient management of large volumes of unstructured data.

Design and implement robust database solutions, ensuring high performance and scalability.

Data Integration and ETL:

Develop and maintain ETL processes to streamline the flow of data across different systems.

Ensure data quality and integrity throughout the integration process.

Collaboration and Communication:

Collaborate with cross-functional teams to understand business requirements and translate them into scalable data solutions.

Communicate effectively with stakeholders to gather and analyze data-related requirements.

Qualifications:

Proven experience as a Data Engineer with a focus on Azure, Spark, Kubernetes, and MongoDB.

Strong expertise in designing and implementing scalable and secure data solutions in a cloud environment.

Proficient in utilizing Spark for data processing and Kubernetes for container orchestration.

Experience with MongoDB, including database design, query optimization, and performance tuning.

Solid understanding of ETL processes and data integration best practices.

Excellent communication skills and the ability to work collaboratively in a team environment.