bebo Technologies is a leading complete software solution provider. bebo stands for 'be extension be offshore'. We are a business partner of QASource, inc. USA[www.QASource.com]. We offer outstanding services in the areas of software development, sustenance engineering, quality assurance and product support. bebo is dedicated to provide high-caliber offshore software services and solutions.

Our goal is to 'Deliver in time-every time'.

For more details visit our website: www.bebotechnologies.com

Let's have a 360 tour of our bebo premises by clicking on below link:

https://www.youtube.com/watch?v=S1Bgm07dPmMKey

Job Responsibilities:

- Develop and maintain scalable data pipelines for batch and real-time data processing
- Build robust data ingestion frameworks using APIs, file-based ingestion, and streaming sources
- Design and implement Python and PySpark-based data transformation logic for large-scale datasets
- Develop Python-based microservices and REST APIs for secure and efficient data access and sharing
- Integrate data pipelines with platforms such as Databricks, Delta Lake, and Snowflake
- Experience with serverless data processing (e.g., AWS Lambda, Azure Functions with Python)
- Implement and manage streaming pipelines using Kafka / Kinesis
- Work with structured, semi-structured, and unstructured data (Parquet,



JSON, CSV, sensor/IoT data)
- Optimize data processing jobs for performance, scalability, and cost efficiency
- Apply best practices for data partitioning, storage optimization, and query performance tuning
- Ensure data quality, validation, and monitoring across pipelines
- Collaborate with data architects, analysts, and downstream consumers to deliver reliable datasets
- Support data modeling and transformation aligned with Lakehouse principles (e.g., medallion architecture)
- Contribute to automation and deployment of pipelines using orchestration and CI/CD practices

Job Requirements:

- 2–4 years of hands-on experience in Data Engineering
- Strong programming expertise in Python and PySpark
- Solid experience in SQL for data transformation and analysis
- Hands-on experience building data pipelines (ETL/ELT) in production environments
- Experience working with APIs and microservices for data ingestion and exposure
- Robust understanding of data processing frameworks such as Spark, AWS Glue, or DBT
- Experience handling large-scale datasets across multiple formats (Parquet, JSON, CSV, or similar)
- Good understanding of Data Lake / Lakehouse concepts and implementation patterns

📌 Software Engineer Data Base (Chandigarh)
🏢 Bebo Technologies
📍 Chandigarh