Senior Data Engineer

Role & responsibilities

• Data Engineering: Design and maintain data pipelines using Python and cloud technologies (AWS, Google Cloud) to ensure efficient data flow and integration across systems.
• Big Data: Work with big data tools such as Hadoop and Kafka to handle large datasets and real-time data streams.
• Data Transformation: Use DBT for transforming raw data into usable formats for analysis and reporting.
• Cloud Infrastructure: Utilize cloud platforms (AWS, Google Cloud) for scalable data storage, processing, and computing.
• AI/ML (Optional): Implement machine learning models and AI algorithms to solve business challenges and provide predictive insights.
• Industry Expertise: Leverage experience across 3-4 industries to understand business needs and translate them into data solutions.

Technical Skills:

• Strong proficiency in Python and experience with data libraries (Pandas, NumPy, Scikit-learn).
• Hands-on experience with NoSQL databases (MongoDB, Cassandra).
• Experience with big data technologies (Hadoop, Kafka) for data processing and streaming.
• Experience with cloud platforms (AWS or Google Cloud) for scalable data solutions.
• DBT experience for data transformation and modelling.

Preferred candidate profile

• Industry Experience: Exposure to at least 3-4 different industries including Finance, Supply Chain Management (SCM), and Healthcare.
• Experience: Minimum of 5 years in data engineering, data science, or related fields.

Perks and benefits

• Flexible Working Hours
• Learn while earn Opportunities
• Positive and Healthy Work Environment
• Open Door Environment
• Opportunity to work On-site
• Rewards and Recognitions
• Fun Fridays
• Best Compensation Structure
• Health Insurance and Life Cover Policy
• Excellent Work-life Balance
• Awarded as Great Place To Work