- Location
- New Delhi, Delhi, India
- Job type
- Full-time
Required skills
- Python
- AWS
- Apache
- Apache Kafka
- Apache Spark
- Azure
- big data technologies
- Cassandra
- cross-functional
- data ingestion
- data pipeline
- Google Cloud
- Hadoop
- HBase
- Java
- Jupyter Notebook
- Kafka
- NoSQL
- NumPy
- Pandas
- SQL
- TensorFlow
- Pytorch
About the role
Tata Consultancy Services
Website:
tcs.com
Job details:
EXPERIENCE- 4-12 YRS
Required Skills:
- PySpark: In-depth knowledge of PySpark, Apache Spark, and Python.
- Data Processing: Strong understanding of data processing concepts, including data ingestion, data transformation, and data storage.
- Cloud Experience: Experience with cloud-based data platforms, including AWS, Azure, or Google Cloud.
- Expertise in DataFrames & Spark SQL, Spark Streaming with Apache Kafka real-time data ingestion pipelines
- Very good conceptual understanding of Multithreading, distributed computing concepts of Pyspark
- Programming: Proficiency in programming languages, including Python, Java, or Scala.
- Communication: Excellent communication and collaboration skills.
Preferred Skills:
- Apache Spark Certifications: Relevant certifications, such as Apache Spark Certification or Cloudera Certified Spark Developer.
- Big Data: Experience with big data technologies, including Hadoop, HBase, or Cassandra.
- Machine Learning: Experience with machine learning frameworks, including TensorFlow, PyTorch, or Scikit-learn.
- Data Science: Experience with data science tools, including Jupyter Notebook, Pandas, or NumPy
Key Responsibilities*
- Data Processing: Design, develop, and maintain data processing solutions using PySpark, Apache Spark, and Python.
- Data Pipeline Development: Develop and optimize data pipelines using PySpark, Apache Spark, and cloud-based data platforms.
- Data Integration: Integrate data from various sources, including relational databases, NoSQL databases, and cloud storage.
- Data Transformation: Develop and implement data transformation logic using PySpark, Apache Spark, and Python.
- Collaboration: Work with cross-functional teams to identify and prioritize project requirements, provide technical guidance, and ensure data quality.
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