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.
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.