Build the outbound engine.

You will be responsible for architecting and developing core application modules using the MERN/MEAN stack (MongoDB, Express, React/Angular, Node.js). This involves designing the database schema for scalability, writing clean RESTful/GraphQL APIs, and integrating them with the frontend UI. Crucially, you own the delivery pipeline: for every feature you write, you must implement the corresponding automated tests (Jest/Mocha) and configure the CI/CD workflow (GitHub Actions/Vercel) to ensure the code passes linting, security checks, and deploys automatically to the staging environment without manual intervention. You are expected to handle environment variables securely and ensure zero-downtime deployments.

You will translate Figma designs and wireframes into responsive, pixel-perfect, and accessible user interfaces. Beyond just "making it look good," you must optimize the application for performance (Core Web Vitals), implementing server-side rendering (SSR) or static site generation (SSG) where appropriate using Next.js. DevOps Integration: You will manage the build processes (Webpack/Vite/Turbopack) to minimize bundle sizes and configure Content Delivery Networks (CDNs) to serve assets globally. You are responsible for setting up automated UI testing (Cypress/Playwright) in the pipeline to catch regression bugs before they reach the main branch.

You will build robust backend services that handle authentication (JWT, OAuth, Session Management) and authorization (RBAC) securely. You must implement input validation (Zod/Joi), rate limiting, and error handling middleware to protect against OWASP Top 10 vulnerabilities. Infrastructure Ownership: You will not just write the server code; you will containerize your application using Docker, defining the Dockerfile and docker-compose.yml to ensure consistency across development and production environments. You are responsible for monitoring application logs and setting up alerts (e.g., Sentry) to catch runtime errors in production immediately.

You will be the gatekeeper of data quality. Your primary task is to write complex, optimized SQL queries (CTEs, Window Functions) and Python scripts (Pandas/Polars) to clean, de-duplicate, and standardize raw datasets from disparate sources (CSVs, APIs, Logs). Automation Focus: You must automate these cleaning routines. Instead of running a script manually, you will schedule these transformation jobs (using Cron or Task Scheduler) to run at specific intervals. You are responsible for building "Data Health Checks" that automatically alert you via email or Slack if the source data contains nulls, anomalies, or schema changes, ensuring the pipeline never fails silently.

You will design and build high-impact, interactive dashboards using Tableau, PowerBI, or Google Looker Studio that answer critical business questions (e.g., Cohort Analysis, CLV, Churn Prediction). Deployment & Maintenance: You are responsible for the "delivery" of these dashboards. This means managing the publishing workspace, setting up scheduled data refreshes, and implementing Row-Level Security (RLS) to ensure users only see what they are authorized to view. You must optimize the underlying data models and extracts to ensure dashboards load in under 2 seconds, even with high data volume, treating the dashboard performance as a production metric.

You will perform deep-dive exploratory analysis to uncover hidden trends, correlations, and actionable insights that are not immediately obvious. You will translate these technical findings into clear, business-facing PDF reports or presentations. Reproducibility: You must document your analysis methodology rigorously using Markdown or Jupyter Notebooks so that any analysis can be re-run or audited instantly. You will maintain a version-controlled repository (Git) of your analysis scripts, ensuring that your logic is preserved and can be "redeployed" for similar future requests without reinventing the wheel.

You will design, develop, and maintain scalable ETL/ELT pipelines to ingest data from various third-party APIs (HubSpot, Shopify, Google Ads), SaaS platforms, and SQL databases into our central data warehouse. DevOps & Orchestration: You must containerize every pipeline using Docker to ensure environment consistency. You will orchestrate these pipelines using tools like Apache Airflow, Prefect, or Dagster. You are responsible for configuring the DAGs (Directed Acyclic Graphs) with retry logic, backfill capabilities, and dependency management so that if an API fails, the system automatically retries and alerts you only if necessary.

You will design structured, efficient data models (Star Schema, Snowflake Schema) within cloud data warehouses like Snowflake, BigQuery, or Redshift. You will write the DDL (Data Definition Language) and manage the schema evolution over time. Infrastructure as Code (IaC): You are responsible for automating the provisioning and management of these resources. You will write scripts to manage warehouse compute sizing (handling scale-up/scale-down) to optimize costs. You must implement role-based access controls (RBAC) via code, ensuring that security policies are applied consistently and automatically across all tables and views.

You will implement a rigorous testing framework for data. This involves writing "Unit Tests for Data" using tools like Great Expectations or dbt tests to validate data integrity (uniqueness, referential integrity, null checks) before it enters the production warehouse. CI/CD for Data: You will integrate these checks into a CI/CD pipeline (GitHub Actions). If a data transformation script breaks a quality rule, the pipeline must block the deployment. You are responsible for setting up an observability dashboard (DataDog/Prometheus) to monitor pipeline latency, failure rates, and row counts, ensuring proactive resolution of issues.