Portfolio Jobs

About Sigma360

Sigma360 is an MIT-incubated, venture-backed, Series B AI-driven global data and analytics company that helps clients manage risk. We convert the world’s messy data into actionable insights for financial institutions, corporates, and governments—powering workflows like name screening, investigations, and risk research.

We are a collaborative team that values ownership, clarity, and practical problem solving.

Why this role matters

Our products depend on large-scale ingestion and transformation of external data. As we expand coverage and ship more AI-driven workflows, we need stronger automated quality checks to ensure our data is accurate, consistent, and trustworthy—from ingestion all the way to what customers see in the UI and API.

This role adds dedicated ownership of data quality and end-to-end data correctness, complementing our existing QA coverage of application features and regression testing.

What you’ll do

You’ll own the testing and validation layer that ensures data quality across ingestion, transformation, and customer-facing outputs.

• Build automated data quality checks on ingested and normalized tables (schema, nulls, duplicates, ranges, consistency)
  
• Validate that source integrations are working as expected (e.g., confirming new content appears on the expected cadence and matches source-of-truth expectations)
  
• Create drift and change detection for recurring ingests (volume deltas, distribution shifts, unexpected changes)
  
• Implement release gates so suspicious or broken data does not ship downstream
  
• Maintain dashboards and alerts so data health is visible and actionable
  
• Partner with data engineering on quality standards, test coverage, and debugging workflows for pipelines and integrations
  
• Partner with QA and backend teams on end-to-end checks confirming the UI/API returns correct, high-quality data (not just that features load)

Tech stack

• Databricks for development, orchestration, and scheduled workflows
  
• Python + PySpark + pandas for pipelines and validation tooling
  
• Data shipped downstream to Postgres and Neo4j, supporting a Golang backend

What we’re looking for

This role is ideal for someone who enjoys building test systems, automating checks, and owning quality end-to-end with a high level of autonomy.

Required:

• 2+ years in a relevant role (QA automation, data engineering, analytics engineering, or similar)
  
• Strong SQL and Python
  
• Strong pandas/dataframe skills (most work is table-based validation and analysis)
  
• Experience designing automated checks and validation logic (test strategy, reliability, failure triage)
  
• Comfort working with production data systems: investigating anomalies, validating outputs, and debugging data issues
  
• Strong written communication and ability to work autonomously in a remote environment
  
• Ability to overlap at least 4 hours with NYC business hours (9am–5pm ET)

Nice to have:

• Experience with Spark / PySpark or Databricks
  
• Familiarity with data quality concepts (expectations, constraints, anomaly detection, drift)
  
• Experience testing APIs or backend services (for end-to-end data correctness)
  
• Experience working with lakehouse/warehouse patterns (Delta Lake, parquet-based pipelines, etc.)
  
• Bachelor’s degree (or equivalent practical experience) in a relevant field

What success looks like (first 6–12 months)

• Core datasets have automated checks that catch issues early and materially reduce data defects reaching production
  
• Source ingest health is continuously validated (freshness, cadence, completeness), and issues are detected quickly with clear reporting
  
• Drift and unexpected changes are visible and actionable (what changed, where, and why it matters)
• Data shipped to backend and displayed in the UI/API is validated against expected behavior and documented standards
  
• Data health signals (dashboards/alerts) become part of normal operating cadence for ingestion and releases

What we offer

• Remote-first team with high autonomy and ownership
  
• Competitive compensation and meaningful equity
  
• Health, dental, vision, and other benefits (or local equivalent)
  
• Generous time off and a culture that supports learning and growth

Sigma360 is an equal opportunity employer. We are committed to fair hiring practices and to creating a welcoming environment for all team members. All qualified applicants will receive consideration without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, familial status, or veteran status.