- Location
- Navi Mumbai, Maharashtra, India
- Job type
- Full-time
Required skills
- Python
- Apache
- Apache Spark
- Artificial Intelligence
- big data technologies
- data modeling
- data models
- ETL
- Hadoop
- Redis
- Spark
- SQL
About the role
Sciative - We Price Right
Website:
sciative.com
Job details:
Job Responsibilities
- Collaborate with data scientists, software engineers, and business stakeholders to understand data requirements and design efficient data models.
- Develop, implement, and maintain robust and scalable data pipelines, ETL processes, and data integration solutions.
- Extract, transform, and load data from various sources, ensuring data quality, integrity, and consistency.
- Optimize data processing and storage systems to handle large volumes of structured and unstructured data efficiently.
- Perform data cleaning, normalization, and enrichment tasks to prepare datasets for analysis and modelling.
- Monitor data flows and processes, identify and resolve data-related issues and bottlenecks.
- Contribute to the continuous improvement of data engineering practices and standards within the organization.
- Stay up-to-date with industry trends and emerging technologies in data engineering, artificial intelligence, and dynamic pricing
Candidate Profile
- Strong passion for data engineering, artificial intelligence, and problem-solving.
- Solid understanding of data engineering concepts, data modeling, and data integration techniques.
- Proficiency in programming languages such as Python, SQL and Web Scrapping.
- Understanding of databases like No Sql , relational database, In Memory database and technologies like MongoDB, Redis, Apache Spark would be add on..
- Knowledge of distributed computing frameworks and big data technologies (e.g., Hadoop, Spark) is a plus.
- Excellent analytical and problem-solving skills, with a keen eye for detail.
- Strong communication and collaboration skills, with the ability to work effectively in a team- oriented environment.
- Self-motivated, quick learner, and adaptable to changing priorities and technologies.
(ref:hirist.tech)
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