Description

Job Description:

Data Engineer is required to be proactive in designing, building and maintaining data systems. The role also requires cross-functional collaborations and ensure highest standards of data quality and performance by extending his expertise in data engineering, data architecture, pipeline creation and big data technologies.

Key Responsibilities:

• Understand the values and vision of the organization.
• Protect the Intellectual Property.
• Adhere to all the policies and procedures.
• Design, develop, and maintain scalable data pipelines for data ingestion, processing and storage.
• Build and optimize data architectures and data models for efficient data storage and retrieval.
• Develop ETL processes to transform and load data from various sources into data warehouses and data lakes.
• Ensure data integrity, quality, and security across all data systems.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Monitor and troubleshoot data pipelines and workflows to ensure high availability and performance.
• Document data processes, architectures, and data flow diagrams.
• Implement and maintain data integration solutions using industry-standard tools and technologies (e.g., Apache Spark, Kafka, Airflow).

Required Skills & Experience:

• Expertise on Data Integration, processing & Storage.
• Expertise on Data optimization architecture, data process and data flow.
• Knowledge of Data integration tools like Apache Spark, Kafka & Airflow.
• Proficiency in SQL and at least one programming language (e.g., Python, Scala).
• Experience with cloud data platforms (e.g., AWS, Azure, GCP) and their data services.
• Experience with data visualization tools (e.g., Tableau, Power BI)

Key Skills

Education

Any Graduate