Narrativ is the marketplace for unbiased product recommendations by experts on the open web. We exponentially increase match rate and augment commerce content with real time conversion data—turning honest recommendations from expert voices into a brand safe, multi-billion dollar acquisition channel.

Demand for expert recommendations has exploded, surpassing the need for simple price comparison and ushering in the era of the Intentional Shopper. This is a lean in, high intent shopper who seeks the whole story to find the products best suited to her individual needs.  

Our product graph—100M+ products mapped to all of the rich stories about them and over $26B of live purchase data —powers our high match rate.  Our market research tools help editors author better, higher converting product recommendations.

Why we’re special:

• Ambitious technology: Our technology mines and organizes the world’s product data in a way that’s useful (rather than intrusive) for consumers. We built a product graph featuring 80mm SKUs enriched with $20bn of monthly cart data, making it the largest database of products matched to product recommendation.
• Talented team: Fast Company recently named Narrativ one of the 50 best workplaces for innovators, fashion disruptor by Financial Times, and a technology pioneer by the World Economic Forum. We’re here to pursue greatness, embrace challenge and relentlessly improve every day.
• Fast growth: Narrativ drove $50mm in revenue for partners like Sephora, Nordstrom, Ulta Beauty, Chanel, Goop, Revolve, and more.

The Job:

A staff data engineer at Narrativ will lead the design and implementation of a first-class data platform. You understand the history of batch and streaming big data systems, know when awk outperforms Hadoop map-reduce, and have spent a lot of time thinking about the best ways to handle schema drift. You care deeply about making scalable systems from simple, reliable, and correct building blocks. You can explain the advantages and disadvantages of a wide range of data structures depending on the desired use case. You can articulate when a general solution is good enough, and when a specialized solution is necessary.

You are Narrativ’s Staff Data Engineer 💽

Mission

• Lead data architecture efforts at Narrativ, from prototype to test to build
• Enable scalability and observability for batch and realtime data streams
• Drive adoption of best practices through mentorship and by example
• Make it simple for the business to find and use data to make decisions

Key Results

• Create a system that captures state changes in Narrativ’s Product Graph and supporting workflows for equality control and analysis purposes.
• Consolidate data architecture into key components (e.g. one streaming system instead of two, one system event bus instead of lossy point-to-point communication)
• Use data schemas well..proper typing, schema registry, handle schema drift, validation
• Create performant straightforward patterns for OLTP, OLAP, streaming ingest and enrichment, creating search indexes, etc
• Manage a merchant product feed that can ingest datasets of 10M+

Requirements:

• 7+ years of experience with big data systems such as Hadoop, Spark, Flink, Kafka, Storm, Heron, NiFi, Hive, etc
• Understanding of different serialization and storage formats like Avro, Parquet, Thrift, Protocol Buffers, FlatBuffers, JSON, CSV, XML
• Working knowledge of relational databases (PostgreSQL, MySQL), non-relational (Redis, Cassandra/Scylla), and warehouses (Snowflake, Redshift, BigQuery)
• Experience with streaming data technologies and patterns
• Experience with orchestration frameworks like Airflow, Oozie
• Expertise in a general purpose programming language
• Strong experience in SQL
• Proven experience leading successful data platform work in multi-team scenarios.

Bonus

• Expertise in Scala, Java, or Kotlin
• Experience in  Elixir
• Working knowledge of probabilistic data structures and algorithms like count-min sketch, hyperloglog, bloom filters, reservoir sampling, etc