Full Stack Software Engineer – Data Observability, Operational Tooling

📋 Description

• Designing and developing front-end interfaces for internal operational tools, which include dashboards, data observability views, and communication surfaces for stakeholders.

• Creating advanced data visualizations that highlight pipeline health, data quality metrics, and business KPIs for both technical and non-technical audiences.

• Establishing and maintaining backend services that support operational tools, integrating with data infrastructure like Snowflake, dbt, and monitoring platforms.

• Collaborating closely with data engineers, analytics engineers, and business stakeholders to transform data observability requirements into user-friendly, high-quality interfaces.

• Functioning independently as a software engineer within a data-oriented team, making technical decisions for the tooling layer while consulting with other full-stack teams across the organization for guidance and support.

• Delivering work iteratively, balancing speed of delivery with code quality, maintainability, and scalability.

⛳️ Requirements

• Proven experience in building and scaling web applications, especially with a strong emphasis on front-end development.

• Deep understanding of contemporary JavaScript/TypeScript frameworks and component-based architectures.

• Experience working with data-intensive interfaces: tables, charts, filters, and interactive visualizations.

• Capability to work autonomously and lead projects from start to finish with minimal supervision.

• Strong programming skills and a history of delivering high-quality software.

• Excellent communication abilities, enabling effective collaboration with data engineers, product managers, and business stakeholders.

• A proactive problem-solving attitude and a strong sense of ownership.

• Familiarity with TypeScript.

• Experience with Svelte or a similar modern component framework (React, Vue).

• Background in constructing data visualization and dashboard interfaces (e.g., D3.js, Chart.js, Plotly, or similar).

• Experience using cloud platforms such as AWS.

• Knowledge of data platforms and tools such as Snowflake, dbt, or similar analytics infrastructure.

• Proficiency in SQL and comfort in working with analytical data sets.

• Experience with Python is advantageous, considering the data team's tooling ecosystem.

• Familiarity with monitoring and observability platforms (e.g., Datadog, Grafana) is a plus.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development