As a Data Engineer at Jai Kisan, you will play a pivotal role in the development and maintenance of our data

infrastructure. You will be responsible for building and optimizing data pipelines, ensuring data accuracy and availability,

and supporting our data-driven initiatives. This role requires expertise in cloud platforms, databases, microservices, and

strong programming skills in Python and SQL.

Roles & Responsibilities:
• Collaborate with cross-functional teams to understand data requirements and translate them into technical

solutions.
• Design, develop, and maintain end-to-end data pipelines, ensuring efficient data extraction, transformation, and

loading (ETL) processes.
• Utilize cloud platforms (AWS, GCP, or Azure) to build, deploy, and manage data solutions in a scalable and

cost-effective manner.
• Develop and maintain microservices for data-related functionalities, allowing for seamless integration with various

applications.
• Implement data quality checks and monitoring processes to ensure data accuracy, consistency, and reliability.
• Perform data modeling and optimization to support reporting, analytics, and machine learning initiatives.
• Work with a variety of databases, including MongoDB, Postgres, and other relational and NoSQL databases.
• Collaborate with data scientists and analysts to enable data-driven decision-making by providing them with clean,

well-structured data.
• Troubleshoot data-related issues and perform root cause analysis to identify and implement solutions.
• Stay updated with emerging technologies and industry best practices in data engineering.

Requirements

Must Have:
• Bachelor's degree in Computer Science, Information Technology, or a related field. 1-2 years of experience in a

data engineering role.
• Strong programming skills in Python and SQL.
• Familiarity with at least one cloud platform (AWS, GCP, or Azure).
• Experience building microservices and deploying them in a cloud environment.
• Proficiency in designing and optimizing data pipelines.
• Knowledge of both relational (e.g., Postgres) and NoSQL databases (e.g., MongoDB).
• Understanding of data modeling concepts.
• Excellent problem-solving and communication skills.
• Ability to work in a fast-paced, collaborative environment.

Good to Have:
• Experience with data orchestration and workflow management tools (e.g., Apache Airflow).
• Knowledge of containerization and orchestration platforms (e.g., Docker, Kubernetes).
• Familiarity with data warehousing solutions (e.g., Amazon Redshift, Google Big Query).
• Exposure to financial data or fintech industry (Optional).
• Strong analytical and data visualization skills.