Note: The job is a remote job and is open to candidates in USA. Hypersonix.ai is disrupting the e-commerce space with AI, machine learning, and advanced decision capabilities to provide real-time business insights. The company is seeking a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure, while collaborating with Data Science, Engineering, and Product teams to support analytics, machine learning, and business applications.
Responsibilities
- Design, develop, and maintain scalable data pipelines for batch and real-time data processing
- Build and optimize ETL/ELT workflows to collect, transform, and load data from multiple sources
- Develop and maintain data models, data warehouses, and data lakes
- Ensure data quality, consistency, accuracy, and reliability across data pipelines
- Optimize data processing workflows for performance, scalability, and cost efficiency
- Work with large and complex datasets from multiple sources
- Collaborate with Data Scientists and ML Engineers to prepare and deliver high-quality datasets for machine learning models
- Develop data integrations with APIs, databases, cloud platforms, and third-party systems
- Monitor data pipelines and troubleshoot data processing and infrastructure issues
- Implement data validation, monitoring, and testing frameworks
- Maintain clear documentation of data pipelines, data models, and technical processes
- Follow best practices for data security, governance, and access control
- Contribute to the design and evolution of Hypersonix's data platform and architecture
Skills
- 5–7 years of experience in Data Engineering or a similar role
- Strong programming skills in **Python** or another programming language
- Strong experience with **SQL** and relational databases
- Hands-on experience building **ETL/ELT pipelines** and data workflows
- Experience with data processing technologies such as **Spark/PySpark**
- Experience working with cloud platforms such as **AWS, Azure, or GCP**
- Good understanding of data warehousing and data lake concepts
- Experience with workflow orchestration tools such as **Airflow, Dagster, or similar**
- Experience working with distributed systems and large-scale datasets
- Strong understanding of data modeling, database design, and performance optimization
- Familiarity with Git and CI/CD practices
- Good understanding of software engineering principles and coding best practices
Company Overview
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