On-Site
Full-Time
Pune, Maharashtra
India
Skills
Amazon Web Services (AWS)
Data Engineering
Extract, Transform, Load (ETL)
Apache Spark
Data Pipelines
Data Integration
Apache
Data Infrastructure
About the Role
Job Title: Data Engineer
Location: Pune (Aundh) - Work From Office
About FPL Technologies:
Credit cards haven't changed much for over half a century so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - a credit card reimagined for the mobile generation. OneCard is India's best metal credit card built with full-stack tech. It is backed by the principles of simplicity, transparency, and giving back control to the user.
Check out OneCard App (Best credit card app) : www.getonecard.app
Opportunity: Join our dynamic and innovative team as a Data Engineer and play a crucial role in shaping the future of our data infrastructure. Contribute to the development and optimization of data pipelines, enabling data-driven decision-making and enhancing the capabilities of our products in the fintech sector.
Experience: 3+ years of experience in Data Engineering
What you'll do:
Collaborate with stakeholders and cross-functional teams to understand data requirements and ensure effective data integration and accessibility across platforms.
Design, build, and optimize data pipelines to extract, transform, and load (ETL) data from diverse sources into data warehouses or other data storage solutions.
Work with big data technologies, such as Hadoop, Spark, or Kafka, to handle large-scale datasets and streamline data processing workflows.
Implement data models and schemas that support the organization’s analytics and reporting requirements, ensuring scalability and performance.
Perform data cleaning, transformation, and aggregation tasks to ensure that data is high-quality, accurate, and ready for analysis.
Monitor and optimize the performance of data pipelines, databases, and other data infrastructure to ensure smooth, efficient, and timely data processing.
Ensure data security and privacy, implementing best practices for secure data storage, transfer, and processing, in compliance with regulatory standards
Collaborate with Data Scientists and Analysts to facilitate the preparation of data for machine learning and business intelligence projects.
Prepare and maintain documentation on data workflows, data models, and any implemented solutions to support troubleshooting and future enhancements.
What you require to have:
Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
Excellent communication skills to collaborate effectively with cross-functional teams and stakeholders.
Strong experience in data engineering, including working with large-scale data pipelines, ETL processes, and data integration frameworks.
Hands-on experience with databases (e.g., PostgreSQL, MySQL, or NoSQL databases) and data warehousing solutions.
Proficiency in Python with a solid understanding of data manipulation and automation libraries.
Proficiency in SQL, with a strong ability to write and understand complex queries for data extraction, transformation, and optimization
Experience with data processing frameworks such as Apache Spark, Apache Kafka, Apache Hive, AWS Glue or similar technologies.
Proficiency in using Apache Airflow to design, schedule, and monitor complex workflows and pipelines or similar orchestration tools
Solid understanding of cloud platforms such as AWS, with hands-on experience in deploying and managing data pipelines in the cloud.
Familiarity with data security best practices, including encryption and access control mechanisms, particularly in a cloud-based environment.
Experience with version control systems, like Git, to manage code and collaborate with teams.
Certifications or coursework in data engineering, cloud computing, or big data technologies are a plus.
Previous experience in the fintech industry or related fields is highly preferred.
FPL Technologies is an Equal Employment Opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender ,disability.
Location: Pune (Aundh) - Work From Office
About FPL Technologies:
Credit cards haven't changed much for over half a century so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - a credit card reimagined for the mobile generation. OneCard is India's best metal credit card built with full-stack tech. It is backed by the principles of simplicity, transparency, and giving back control to the user.
Check out OneCard App (Best credit card app) : www.getonecard.app
Opportunity: Join our dynamic and innovative team as a Data Engineer and play a crucial role in shaping the future of our data infrastructure. Contribute to the development and optimization of data pipelines, enabling data-driven decision-making and enhancing the capabilities of our products in the fintech sector.
Experience: 3+ years of experience in Data Engineering
What you'll do:
Collaborate with stakeholders and cross-functional teams to understand data requirements and ensure effective data integration and accessibility across platforms.
Design, build, and optimize data pipelines to extract, transform, and load (ETL) data from diverse sources into data warehouses or other data storage solutions.
Work with big data technologies, such as Hadoop, Spark, or Kafka, to handle large-scale datasets and streamline data processing workflows.
Implement data models and schemas that support the organization’s analytics and reporting requirements, ensuring scalability and performance.
Perform data cleaning, transformation, and aggregation tasks to ensure that data is high-quality, accurate, and ready for analysis.
Monitor and optimize the performance of data pipelines, databases, and other data infrastructure to ensure smooth, efficient, and timely data processing.
Ensure data security and privacy, implementing best practices for secure data storage, transfer, and processing, in compliance with regulatory standards
Collaborate with Data Scientists and Analysts to facilitate the preparation of data for machine learning and business intelligence projects.
Prepare and maintain documentation on data workflows, data models, and any implemented solutions to support troubleshooting and future enhancements.
What you require to have:
Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
Excellent communication skills to collaborate effectively with cross-functional teams and stakeholders.
Strong experience in data engineering, including working with large-scale data pipelines, ETL processes, and data integration frameworks.
Hands-on experience with databases (e.g., PostgreSQL, MySQL, or NoSQL databases) and data warehousing solutions.
Proficiency in Python with a solid understanding of data manipulation and automation libraries.
Proficiency in SQL, with a strong ability to write and understand complex queries for data extraction, transformation, and optimization
Experience with data processing frameworks such as Apache Spark, Apache Kafka, Apache Hive, AWS Glue or similar technologies.
Proficiency in using Apache Airflow to design, schedule, and monitor complex workflows and pipelines or similar orchestration tools
Solid understanding of cloud platforms such as AWS, with hands-on experience in deploying and managing data pipelines in the cloud.
Familiarity with data security best practices, including encryption and access control mechanisms, particularly in a cloud-based environment.
Experience with version control systems, like Git, to manage code and collaborate with teams.
Certifications or coursework in data engineering, cloud computing, or big data technologies are a plus.
Previous experience in the fintech industry or related fields is highly preferred.
FPL Technologies is an Equal Employment Opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender ,disability.