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Data Engineer
WN Infotech
posted 5d ago
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Job Description
As a Data Engineer at Web Neural Infotech, you will play a pivotal role in designing, building, and maintaining robust data pipelines and architectures that power AI, ML, and Big Data applications. Your responsibilities will include handling large datasets, optimizing data workflows, and ensuring data availability and quality for analytics and decision-making.
This role is ideal for freshers passionate about working with data and experienced professionals eager to contribute to cutting-edge projects in a dynamic and innovative environment.
- Data Pipeline Development : Design, implement, and maintain scalable data pipelines for processing structured and unstructured data.
- Data Integration : Integrate data from diverse sources such as APIs, databases, and third-party platforms into unified data models.
- ETL Processes : Develop and optimize Extract, Transform, Load (ETL) workflows for data processing.
- Data Architecture : Design and maintain data architectures to support analytics, reporting, and data science needs.
- Big Data Solutions : Work with Big Data technologies like Hadoop, Spark, or Kafka to handle massive datasets efficiently.
- Database Management : Optimize and manage relational and NoSQL databases, ensuring data integrity and availability.
- Collaboration : Work closely with data scientists, analysts, and developers to ensure seamless data flow and accessibility.
- Data Security : Implement data governance policies and ensure compliance with security and privacy regulations.
- Performance Optimization : Monitor and improve the performance of data processing workflows.
- Programming Languages : Proficiency in Python, Java, or Scala for data processing and workflow automation.
- Data Pipeline Tools : Experience with tools like Apache Airflow, NiFi, or Talend for building workflows.
- Big Data Technologies : Familiarity with Hadoop, Spark, Kafka, or similar platforms for large-scale data processing.
- Database Management : Knowledge of SQL, NoSQL databases (e. g. , MongoDB, Cassandra), and data warehouses (e. g. , Redshift, Snowflake).
- Cloud Platforms : Experience with cloud services like AWS, Azure, or Google Cloud for data storage and processing.
- ETL Development : Strong understanding of ETL tools and frameworks for efficient data transformation.
- Data Modeling : Skills in designing normalized and denormalized data models for analytics.
- Version Control : Proficiency with Git for managing and versioning codebases.
- Education : Bachelor s degree in Computer Science, Data Engineering, or related fields. A Master s degree is a plus.
- Certifications (Preferred) :
- Certifications like AWS Certified Data Analytics - Specialty , Google Cloud Professional Data Engineer , or equivalent.
- Experience :
- Freshers with strong foundational knowledge and hands-on projects in data engineering are encouraged to apply.
- 1-3 years of experience in data engineering or a related role is preferred.
Employment Type: Full Time, Permanent
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