Data Engineer

Data Engineer with strong Python expertise

Key Responsibilities:

• Develop, test, and maintain scalable data pipelines.
  
• Write efficient, reusable Python code for data processing.
  
• Work with structured and unstructured data using Pandas, PySpark, or Dask.
  
• Integrate with databases (SQL and NoSQL) for data extraction and transformation.
  
• Deploy and manage data workflows on cloud platforms (AWS, Azure, GCP).
  
• Collaborate with analytics and product teams to optimize data delivery and reliability.
  

Core Technical Skills:

Core Python Skills

• Data structures: Lists, dictionaries, sets, tuples
  
• Functions & OOP: Writing reusable code, classes, inheritance
  
• Error handling: Try-except blocks, logging
  
• File I/O: Reading/writing CSV, JSON, Parquet, etc.
  

Data Engineering Tools & Libraries

• Pandas, NumPy, SQLAlchemy
  
• PySpark for big data processing
  
• Dask for parallel computing
  

Database & Querying

• SQL: Writing efficient queries, joins, aggregations
  
• Relational databases: PostgreSQL, MySQL, MS SQL Server
  
• NoSQL databases: MongoDB, Cassandra, Redis
  

Cloud Platforms

• AWS: S3, Lambda, Redshift
  
• Azure: Data Factory, Blob Storage
  
• Google Cloud: BigQuery, Cloud Functions
  

Educational Qualification:

B.Tech / B.E / M.Tech / MCA in Computer Science, Information Technology, or related field.

Desired Candidate Profile:

• Strong problem-solving and debugging skills.
  
• Excellent understanding of data structures and algorithms.
  
• Familiarity with version control (Git) and CI/CD processes.
  
• Strong communication and collaboration abilities.
  

Benefits:

• Competitive salary and performance bonuses.
  
• Flexible working hours and remote-friendly culture.
  
• Health insurance and learning allowances.
  
• Exposure to large-scale data projects and modern tech stacks.