Applications Engineer

Roles and responsibilities

1. Design and Development of Data Applications

   • Develop and design applications that process, analyze, and visualize data, often for specific business needs or functions (e.g., financial reporting, customer behavior analysis, etc.).
   • Build data pipelines and workflows to ingest, process, and store large volumes of data efficiently.
   • Implement data processing solutions using technologies like Apache Hadoop, Spark, or Kafka.

2. Database and Data Management

   • Work closely with databases and data storage solutions, including both relational (SQL) and non-relational (NoSQL) databases such as MySQL, MongoDB, or Cassandra.
   • Develop and optimize queries for efficient data retrieval and manipulation.
   • Ensure the scalability, reliability, and security of data storage solutions.

3. Data Integration

   • Integrate various data sources from internal and external systems into centralized data platforms.
   • Work with APIs and other data connectors to integrate disparate data sources seamlessly.
   • Create data pipelines that combine data from multiple sources for processing and analytics.

4. Optimization and Performance Tuning

   • Analyze and optimize the performance of data processing and application systems to ensure efficient data handling and minimal latency.
   • Improve the speed, accuracy, and scalability of data applications through system optimization.
   • Monitor and resolve performance bottlenecks in large data environments.

5. Data Analysis and Visualization

   • Design and implement data models for reporting and analytical applications.
   • Create data visualizations and dashboards using tools like Tableau, Power BI, or custom-built applications to present data insights to stakeholders.
   • Provide insights from data and help interpret the results to guide decision-making processes.

6. Collaboration with Other Teams

   • Work closely with data scientists, analysts, and business intelligence teams to understand data requirements and design appropriate data solutions.
   • Collaborate with software development teams to integrate data applications with front-end systems and user interfaces.
   • Communicate technical information effectively to non-technical stakeholders to ensure alignment with business goals.

7. Data Security and Compliance

   • Ensure that data applications adhere to legal and regulatory compliance requirements, such as GDPR, HIPAA, etc.
   • Implement security protocols to protect sensitive data, ensuring that data is encrypted and access is appropriately managed.
   • Regularly audit and update systems to comply with data privacy regulations.

8. Testing and Quality Assurance

   • Implement unit and integration tests for data-driven applications to ensure correctness, reliability, and performance.
   • Debug and troubleshoot data-related issues in applications, identifying root causes and providing solutions.

9. Documentation

   • Document the architecture, development process, and functionalities of data applications to ensure maintainability and ease of knowledge transfer.
   • Provide technical support documentation for users and developers to understand how to use and maintain the systems.

10. Stay Updated with Industry Trends

    • Continuously learn about emerging data technologies, tools, and best practices to keep the application systems up to date.
    • Investigate and implement new techniques or frameworks to improve the efficiency and capabilities of data processing systems.

Desired candidate profile

This role sits at the intersection of data engineering, software development, and application design, offering the opportunity to build scalable, high-performance systems for data-intensive use cases.

Responsible for designing, building, and maintaining scalable data pipelines and platforms, ensuring the seamless flow of data across systems, and supporting advanced analytics and business intelligence needs.

ROLE PROFILE

• Design and maintain scalable data solutions focused on deriving actionable KPIs and business metrics.
• Collaborate with teams to automate and deliver KPIs for cross-functional stakeholders.
• Build and enhance engineering frameworks on e-commerce data, including sales, marketing, retail media, clickstream, and customer insights, to drive business performance.
• Monitor data applications to ensure seamless operations, minimizing downtime and errors for critical reports.
• Optimize data transformation processes using best practices, ensuring efficiency and accuracy in KPI generation.
• Identify opportunities to automate processes within data workflows and applications for improved efficiency.
• Assist in backend development and implementation of interactive data applications to facilitate customer friendly B2B and B2C data offerings.

REQUIREMENTS

• Bachelor's degree in engineering and/or Science
• 5+ years of experience in Data Engineering, Data warehousing and Data applications development,
• Strong with SQL, Python, OOPs concepts, Web Apps
• Experience in GCP platform (Airflow, Composer, Big Query, Pub Sub, Cloud Run, Web Hosting)
• Experience in working with API endpoints (GET and POST)