The role
Position: Python Analytics Dashboard & Application Developer
Contract type: Permanent / Full Time
Reporting to: Head of Data
Location: Mumbai, India
Overview of role
Python Analytics Dashboard Developer sits at the intersection of data analytics and application development. You will design and build interactive, analytically rich web applications using Dash, connecting to Databricks Lakehouse as the data backend.
Our data engineering team manages all upstream data pipelines and transformations. Your focus is entirely on the application layer — building polished, user-friendly dashboards and data entry tools that bring already-prepared data to life through great UX and insightful visualisations.
This role is ideal for someone who started in data analytics and has grown into building Python-based applications — someone who understands the meaning of data as well as how to display it.
Key responsibilities and primary deliverables
- Design and develop interactive web applications using Dash (Python), with clean and intuitive layouts
- Build interactive charts and visualisations using Plotly — scatter plots, bar charts, line charts, KPI cards, drill-downs — that clearly communicate analytical insights to business users
- Apply custom CSS and Dash Bootstrap Components to deliver professional, branded UI designs including navigation bars, modals, cards, and styled forms
- Build data entry forms and editable data tables that allow users to input and correct data directly within the application
- Implement data writeback patterns (INSERT / MERGE / UPSERT) to Databricks Delta tables, with audit trails capturing user, timestamp, and change details
- Perform light data wrangling within the application layer using Pandas — reshaping, filtering, and aggregating query results before passing to visualisations
- Handle input validation on both the UI and Python backend before committing data changes
- Deploy applications to Databricks Apps
- Write clean, well-commented, and maintainable code structured with clear separation of concerns (data access layer, chart logic, app layout)
- Collaborate with our data engineering and analytics teams to understand table structures, schemas, and KPI definitions
Skills profile
Relevant experience & education
- 5+ years of combined experience in data analytics and Python application or dashboard development
- Demonstrable experience building applications or dashboards with Plotly / Streamlit / Seaborn Dash — including multi-page apps, callbacks, and state management
- Experience building multi-page Dash apps with sidebar navigation
- Strong data analytics background — comfortable working with business KPIs, interpreting datasets, and selecting the right chart type for the right metric
- Solid SQL skills — writing queries to read, filter, aggregate, and write data against relational or cloud data warehouse tables
- Proficiency in Pandas for data manipulation and transformation within application logic
- Strong CSS skills — writing custom stylesheets and applying component-level styling
- Hands-on experience with Dash Bootstrap Components or equivalent CSS frameworks (Bootstrap, Tailwind) to build polished, responsive layouts
- Proficiency in Power BI or Tableau — building reports and dashboards connected to a cloud data warehouse or SQL data source
- Proficiency with Git for version control
Databricks Requirements
Deep data engineering expertise is not required. The focus is on connecting a Dash application to Databricks and reading/writing data from existing, already-prepared tables.
Specifically, the candidate should be able to:
- Connect a Python application to a Databricks SQL Warehouse via connection string and personal access token
- Write SQL queries against Delta tables — SELECT, INSERT, MERGE/UPSERT
- Understand basic Delta Lake behaviour — table versioning, safe writes
- Navigate the Databricks UI to browse catalogs, preview tables, and verify query results
- Deploy and configure a Python app on Databricks Apps using Gunicorn
Nice to Have
- Experience with Azure Databricks specifically
- Understanding of audit trail and data governance patterns for data entry applications
- Exposure to Streamlit or similar Python-based dashboard frameworks
- Basic knowledge of React or JavaScript — useful for potential future framework evolution
Soft Skills
- Strong analytical mindset — able to look at data and ask does this make sense before presenting it
- An eye for data visualisation best practices — knowing which chart type best communicates a given insight, not just how to build one
- Attention to detail in both UI quality and data accuracy
- Good written and verbal communication skills in English
- Ability to work independently and manage deadlines in a remote setting
- Proactive in surfacing questions and flagging blockers early
- Takes pride in writing clean, well-documented, maintainable code
Due to the high volume of applications, we regret that only shortlisted candidates will be contacted.