Zingbus - Data Engineer - Python

Founded in 2019, zingbus is building the most trusted brand for intercity travel. Keeping reliability and safety at the core, we are building a two-sided platform that delivers standardized journey experience for travelers and increased earnings for our supply partners.

We connect 300+ cities acrossthe country through our daily services and have served 2.5 Mn+ unique customers so far and are aggressively working towards the fleet electrification and establishment of charging technology and infrastructure.

Raised Series A from Y Combinator, InfoEdge, AdvantEdge, and other prominent investorsfrom India and Silicon Valley. Additionally, secured a significant investment of $9 million from bp : Data Engineer

Location : Gurgaon

Education : Preferred : Tier 1 - BTech (Preferably)

Key Responsibilities

• Develop, optimize and maintain scalable data pipelines for efficient data flow and transformation.
• Design error handling and visibility solutions for monitoring pipeline health and failures.
• Work with structured and unstructured data, ensuring data integrity and consistency.
• Collaborate with cross-functional teams, including data scientists, analysts and engineers to understand data needs and provide solutions.
• Ensure high performance and reliability of data infrastructure while automating data processing tasks.
• Optimize data retrieval, storage and processing methodologies to enhance system efficiency.
  
  

Required Skills & Qualifications

• Proficiency in Python or any scripting language (e.g., Bash, Perl, JavaScript, or Shell scripting).
• Strong debugging and troubleshooting skills with a focus on performance optimization.
• Strong understanding of logic control, algorithms and data structures.
• Experience in developing end-to-end data processing solutions.
• Ensure compliance with data governance and security standards.
• Hands-on experience in ETL pipelines, workflow orchestration tools (e.g., Airflow), and data warehousing solutions.
• Familiarity with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Kafka, Hadoop, etc.).
• Experience with database management systems such as SQL, NoSQL or columnar databases.
• Knowledge of CI/CD pipelines and version control systems (Git, GitHub, Bitbucket).
  
  

Preferred Qualifications

• Familiarity with real-time data streaming and event-driven architectures.
• Exposure to monitoring tools like Grafana or ELK stack.
• Basic knowledge of machine learning workflows and MLOps practices.
  
  

Why Join Us

• Work on cutting-edge data engineering projects that drive business growth.
• Opportunity to innovate and optimize data infrastructure at scale.
• Collaborative and growth-oriented work environment.)
  
  

(ref:hirist.tech)