Jobs at Alternative Path

Analyze and enhance commercial investment data by identifying dataset gaps, sourcing and validating information, writing SQL queries, cleaning large datasets, and building dashboards and reports. The role translates business requirements into analytical tasks, uses AI agents and tools to automate data workflows, supports ad hoc analyses, documents data processes, and presents actionable findings to nontechnical stakeholders.

Performs functional, regression, integration, API, and end-to-end testing; develops and maintains Playwright automation; investigates defects and root causes; and collaborates across Agile delivery teams. The role also applies AI throughout test planning, case generation, automation, defect analysis, regression optimization, and evaluation of AI-generated outputs. Candidates will build reusable AI workflows, Skills, or Agents and improve testing coverage, reliability, and efficiency.

Design, develop, test, deploy, and maintain full-stack client applications across databases, APIs, frontends, and cloud infrastructure. Build Node.js and Python backend services, ReactJS interfaces, and MySQL/PostgreSQL databases. Use LLM-assisted development tools, manage applications post-launch, contribute to architecture decisions, collaborate directly with clients, and support multiple engagements through debugging, enhancements, performance tuning, documentation, and code reviews.

Design and implement Python-based automation for configuring data quality checks across vendor datasets. Use LLMs, documentation, and machine learning to identify critical fields and establish quality thresholds. Collaborate with data managers and software engineers to improve data-check coverage, resolve requirements, and support existing feeds. Develop dashboards tracking data quality coverage and compliance. The role requires enterprise Python development, Pandas-based transformations, SQL exposure, and preferably AWS, Kubernetes, S3, and Trino experience.

Design and maintain web scrapers for alternative datasets, clean and transform large data sets using Python and Pandas, and ingest data into databases or warehouses. Build scheduled workflows with Airflow, create quality-control checks, maintain alerting systems, investigate data incidents, and develop tools for the web-scraping platform. Collaborate with analysts and cross-functional teams to deliver reliable datasets and data products.

Design, maintain, and improve web scrapers for alternative datasets; clean, transform, validate, and load data into databases or warehouses; orchestrate pipelines with Airflow; and build quality checks, alerts, and data tools. Collaborate with analysts and cross-functional teams to define data requirements, investigate time-sensitive incidents, and support investment decision-making through reliable datasets and notifications.