Bangalore, Karnataka, India
Information Technology
Full-Time
CoffeeBeans
Overview
Experience: 1-3 year
Location: Bangalore/Pune/Hyderabad
Work mode: Hybrid
Founded in the year 2017, CoffeeBeans specializes in offering high end consulting services in technology, product, and processes. We help our clients attain significant improvement in quality of delivery through impactful product launches, process simplification, and help build competencies that drive business outcomes across industries. The company uses new-age technologies to help its clients build superior products and realize better customer value. We also offer data-driven solutions and AI-based products for businesses operating in a wide range of product categories and service domains
As a Data Engineer, you will play a crucial role in designing and optimizing data solutions for our clients. The ideal candidate will have a strong foundation in Python, experience with Databricks Warehouse SQL or a similar Spark-based SQL platform, and a deep understanding of performance optimization techniques in the data engineering landscape. Knowledge of serverless approaches, Spark Streaming, Structured Streaming, Delta Live Tables, and related technologies is essential.
What are we looking for?
Design, develop, and maintain scalable and efficient data solutions.
Collaborate with clients to understand data requirements and provide tailored solutions.
Implement performance optimization techniques in the data engineering landscape.
Work with serverless approaches to enhance scalability and flexibility.
Utilize Spark Streaming and Structured Streaming for real-time data processing.
Implement and manage Delta Live Tables for efficient change data capture.
Location: Bangalore/Pune/Hyderabad
Work mode: Hybrid
Founded in the year 2017, CoffeeBeans specializes in offering high end consulting services in technology, product, and processes. We help our clients attain significant improvement in quality of delivery through impactful product launches, process simplification, and help build competencies that drive business outcomes across industries. The company uses new-age technologies to help its clients build superior products and realize better customer value. We also offer data-driven solutions and AI-based products for businesses operating in a wide range of product categories and service domains
As a Data Engineer, you will play a crucial role in designing and optimizing data solutions for our clients. The ideal candidate will have a strong foundation in Python, experience with Databricks Warehouse SQL or a similar Spark-based SQL platform, and a deep understanding of performance optimization techniques in the data engineering landscape. Knowledge of serverless approaches, Spark Streaming, Structured Streaming, Delta Live Tables, and related technologies is essential.
What are we looking for?
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 1-3 year of experience as a Data Engineer.
- Proven track record of designing and optimizing data solutions.
- Strong problem-solving and analytical skills.
- Python: Proficiency in Python for data engineering tasks and scripting.
- Performance Optimization: Deep understanding and practical experience in optimizing data engineering performance.
- Serverless Approaches: Familiarity with serverless approaches in data engineering solutions.
- Databricks Warehouse SQL or Equivalent Spark SQL Platform: Hands-on experience with Databricks Warehouse SQL or a similar Spark-based SQL platform.
- Spark Streaming: Experience with Spark Streaming for real-time data processing.
- Structured Streaming: Familiarity with Structured Streaming in Apache Spark.
- Delta Live Tables: Knowledge and practical experience with Delta Live Tables or similar technologies.
Design, develop, and maintain scalable and efficient data solutions.
Collaborate with clients to understand data requirements and provide tailored solutions.
Implement performance optimization techniques in the data engineering landscape.
Work with serverless approaches to enhance scalability and flexibility.
Utilize Spark Streaming and Structured Streaming for real-time data processing.
Implement and manage Delta Live Tables for efficient change data capture.
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