Senior Data Engineer - Fast, Scalable Market Data Platform

Polygon.io; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

Massive is building a data platform that turns raw market data into fast, well-shaped datasets. You will own the data modeling, transformation, and API surface that customers query for insights.

This full‑stack data role covers ingestion of third‑party feeds and the center of gravity: cleaning, modeling, and efficient storage as volume grows. You’ll wear multiple hats and ship production data assets used by teams.

Qualifications

• Strong Python and SQL skills; daily use of both for data work.
• Experience modeling analytical data; normalize vs. denormalize decisions.
• Proven track record making tables and queries faster via partitioning and layout.
• Hands-on with modern analytical engines or lakehouses (e.g., DataFusion, Snowflake).
• Comfort with columnar formats (Parquet/Iceberg/Delta) and object storage.

Responsibilities

• Model the data: design entities, relationships, grains, and rationale.
• Build and own the transformation layer in Python and SQL; clean, normalize, validate, reconcile.
• Ingest from external APIs; handle rate limits, pagination, incremental loads, and backfills.
• Preserve raw provider data; layer cleaned/curated data on top.
• Make it fast: partitioning, sorting, clustering, and indexing; profile with EXPLAIN plans.
• Partner with Product to design API surfaces for datasets; define performance and pagination semantics.
• Collaborate with Data Science/AI Engineering on datasets and features used by models.
• Set quality bar: ingest validation, drift detection, freshness, documented assumptions.

Skills

Python

SQL

Data modeling

Data warehousing

API design

Tools

DataFusion

DuckDB

Databricks

Snowflake

BigQuery

Job description

Massive is building a data platform that turns raw market data into fast, well-shaped datasets. You will own the data modeling, transformation, and API surface that customers query for insights.

This full‑stack data role covers ingestion of third‑party feeds and the center of gravity: cleaning, modeling, and efficient storage as volume grows. You’ll wear multiple hats and ship production data assets used by teams.