SENIOR FULLSTACK DEVELOPER

Job Summary:
We are seeking a seasoned “Senior Full Stack Engineer” to lead a development team. In this
role, you'll architect and build high-performance web applications or components used to centralize the discovery,
governance, and usage management across the data and analytics ecosystem. You’ll work across the stack using Java
(Spring Boot), Angular/React etc., and Relational and/or Graph databases, and collaborate with product owners, product
managers, and business stakeholders to deliver scalable, insightful solutions.
You’ll also play a key role in driving the technical direction, mentoring junior engineers, and ensuring best practices in
performance, security, and usability.

Responsibilities:
Lead the design and development of full-stack analytics tools, dashboards, and self-service data products.
Build backend APIs and services that aggregate and serve data efficiently.
Design responsive and intuitive frontend interfaces using Angular for real-time data interaction and visualization.
Optimize SQL queries and work closely with data engineers on schema design and performance tuning.
Collaborate with stakeholders to translate analytical requirements into robust technical solutions.
Mentor junior developers and review code for maintainability and performance.
Drive adoption of best practices in testing, deployment, and code quality.

Requirements:
5+ years of full-stack development experience, ideally in a data-centric environment.
Expertise in Java (Spring Boot), Angular (v16+)/React, and SQL and/or graph databases.
Strong experience building web-based data applications or internal tools used for analytics.
Familiarity with common data patterns, ETL workflows, and working with large datasets.
Experience with RESTful APIs, caching strategies, and performance tuning.
Strong understanding of data privacy and security concerns in analytics applications.
Excellent communication skills and ability to collaborate with non-technical users.

Preferred:
Experience integrating with data lakes, warehouses, or BI tools.
Familiarity with data visualization tools (e.g., Tableau, Power BI, Qlik Sense, or embedded dashboards).
Knowledge of cloud platforms (AWS, Azure, Google Cloud).
Knowledge of cloud-based data platforms (AWS Redshift, Azure Synapse, Google BigQuery).
Understanding of event-driven or streaming architectures (Kafka, Spark, etc.).