Hybrid Senior Data Engineer

at Monstro

• Job title: Senior Data Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: $160,000 - $200,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Cloud, ETL, Python, SQL
• Location requirements: Hybrid, New York City, United States

About the role

• Senior Data Engineer building scalable data pipelines at Monstro, an innovative fintech company. Shape the future of data architecture in a data-intensive environment.

Responsibilities

• Build and own scalable pipelines that parse and normalize unstructured sources for retrieval, knowledge graphs, and agents.
• Conceive and implement novel processes for processing thousands of types of unstructured documents with accuracy and consistency.
• Process semi structured sources into consistent, validated schemas.
• Transform structured datasets for analytics, features, and retrieval workloads.
• Create, version, and maintain multiple collections in a vector database.
• Manage embeddings, metadata, and lifecycle, and tune chunking and filters for relevance and latency.
• Design and implement robust multi-modal document processing systems that handle heterogeneous file formats (PDFs, images, HTML, XML).
• Own ingestion from APIs, file drops, partner feeds, and scheduled jobs with monitoring, retries, and alerting.
• Implement data quality checks for schema, ranges, and nulls, and document lineage and SLAs.
• Stand up and harden object, relational, document, and vector stores with the right indexing and partitioning.
• Build reusable libraries and services for parsing, enrichment, and embedding generation.
• Handle sensitive financial and personal data with access controls, auditing, and retention policies.
• Partner with product and engineering to ship features that depend on reliable data.
• Document standards, coach teammates, and contribute to future hiring.

Requirements

• Minimum 2 years in a dedicated Data Engineering role at an AI-native startup or 4+ years of experience in traditional Data Engineering, with ~8+ years of experience in Tech overall.
• Proven ownership of end-to-end pipelines (ingestion → transformation → serving), including scalable sourcing processes, ETL pipelines, and serving services.
• Experience owning and operating infrastructure in production environments.
• Strong Python and SQL.
• Hands on document parsing and ETL across PDFs, HTML, JSON, and XML.
• Experience operating vector databases such as pgvector, Pinecone, or Weaviate, with multiple collections.
• Building and scheduling ingestion via APIs, web downloads, and cron or an orchestrator, plus cloud storage and queues.
• Understanding of embeddings, chunking strategies, metadata design, and retrieval evaluation.
• Solid data modeling, schema design, indexing, and performance tuning across storage types.
• History of implementing data quality checks, observability, and access controls for sensitive data.
• Track record of delivering high-consistency systems for mission-critical data pipelines.
• Ownership mindset, clear written communication, and effective collaboration with product and engineering.

Benefits

• Equity
• Flexible work arrangements