
Bigdata specialist programmer
About the role
Key Responsibilities:
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Lead the design and implementation of big data solutions using Spark, Pyspark, Hive, and Scala.
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Collaborate with cross-functional teams to develop scalable data architectures and pipelines.
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Optimize data processing workflows to ensure high performance and reliability.
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Mentor and guide junior engineers, fostering a culture of continuous learning and improvement.
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Ensure data security and compliance with industry standards.
Minimum Qualifications:
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Bachelor's degree in Technology (B.Tech) or related field.
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Proven experience in big data technologies such as Spark, Pyspark, Hive, and Scala.
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Strong analytical and problem-solving skills.
Preferred Qualifications:
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Experience with Kafka for real-time data processing.
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Demonstrated leadership skills in managing technology projects.
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Ability to work effectively in a collaborative team environment.
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Track record of delivering high-quality data solutions.
Good to have skills:
Flask, Pandas, Data Analysis, Springboot, Microservices
- Knowledge of more than one technology
- Basics of Architecture and Design fundamentals
- Knowledge of Testing tools
- Knowledge of agile methodologies
- Understanding of Project life cycle activities on development and maintenance projects
- Understanding of one or more Estimation methodologies, Knowledge of Quality processes
- Basics of business domain to understand the business requirements
- Analytical abilities, Strong Technical Skills, Good communication skills
- Good understanding of the technology and domain
- Ability to demonstrate a sound understanding of software quality assurance principles, SOLID design principles and modelling methods
- Awareness of latest technologies and trends
- Excellent problem solving, analytical and debugging skills
Education: MSc,MTech,Bachelor of Engineering,BTech
- Preferred skills: Technology->Big Data
- Data Processing->Spark,Technology->Big Data
- Data Processing->Py Spark,Technology->Functional Programming->Scala
About Infosys
BANGALORE
Headquarters