Job Description

Responsibilities :
Key Responsibilities (Common Across Roles)
1. Design and develop data pipelines, ETL processes, and analytical solutions.
2. Collaborate with cross-functional teams to understand business requirements and deliver scalable solutions.
3. Ensure compliance, security, and performance in data solutions.
4. Communicate effectively with stakeholders and present technical solutions clearly.
5. Work in Agile environments and contribute to CI/CD practices.
Role-Specific Responsibilities - Data Scientist
1. Build and deploy machine learning models and AI solutions.
2. Perform statistical analysis, hypothesis testing, and data exploration.
3. Work on NLP, computer vision, and deep learning use cases.
4. Utilize frameworks like TensorFlow, PyTorch, Scikit-Learn, BERT.
Role-Specific Responsibilities - Azure Data Engineer
1. Develop data pipelines using Python, PySpark, Pandas on Azure.
2. Work with Azure Data Factory, Databricks, Synapse, Data Lake, Azure SQL/DWH.
3. Implement DevOps practices, CI/CD pipelines, and manage code with Git.
Role-Specific Responsibilities - AWS Data Engineer
1. Build data pipelines using Python, PySpark, Pandas on AWS.
2. Work with AWS Lambda, Glue, Athena, Redshift, Kinesis, EMR, S3.
3. Experience with Airflow DAGs, Snowflake/Redshift, and test frameworks like Pytest.
Additional Responsibilities :
Locations Offered: Bengaluru, Hyderabad, Chennai, Noida, Gurgaon, Chandigarh, Pune, Nagpur, Mumbai, Trivandrum, Mysuru, Coimbatore, Indore, Kolkata, Bhubaneswar
Technical and Professional Requirements :
Eligibility & Requirements
Common Requirements
1. Strong programming skills in Python (Java/R for some roles).
2. Expertise in SQL and relational databases (Oracle, PostgreSQL, SQL Server).
3. Bachelor's/Master's degree in Computer Science, IT, Statistics, or related field.
4. Excellent communication and problem-solving skills.
Eligibility & Requirements - Data Scientist
1. 5-18 years of experience in Data Science.
2. Strong knowledge of ML algorithms (Regression, Random Forest, SVM, Neural Networks).
3. Exposure to Deep Learning, NLP, and Computer Vision.
Eligibility & Requirements - Azure Data Engineer
1. 5-18 years of experience in Data Engineering.
2. Hands-on with Azure ecosystem (ADF, Databricks, Synapse, Data Lake).
Eligibility & Requirements - AWS Data Engineer
1. 5-18 years of experience in Data Engineering.
2. Hands-on with AWS ecosystem (Glue, Lambda, Redshift, Kinesis, EMR).
Preferred Skills :
Technology->Machine learning->data science,Technology->Machine Learning->Python,Technology->Cloud Platform->Azure Analytics Services->Azure Data Factory,Technology->Data Engineering->Databricks
Educational Requirements :
Bachelor of Engineering,Bachelor Of Technology
Service Line :
Infosys Consulting

Skills Required