Everway

Principal Data Engineer (Product Data)

Rol remoto de Data Engineering con fit claro de ubicación del candidato.

Publicado7 jul 2026

Países elegibles41 países aceptados

Señal de senioritySenior

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Actualidad de la fuente7 jul 2026

Fit de ubicación41 países aceptados

Match de stackCI/CD, Python

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Aplicando aPrincipal Data Engineer (Product Data)Everway

Fit de país41 países aceptados

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Design and deliver product data products on Databricks — owning ingestion, transformation, and serving layers across the medallion architecture (bronze/silver/gold) to produce certified datasets consumed across product, analytics, and the wider business
Lead the hard problems in the domain — event schema governance across multiple products, identity resolution and sessionisation, high-volume event pipelines, and modelling the path from product usage to engagement and learner outcomes
Define and evolve engineering standards — dbt patterns, event ingestion patterns, data contracts, testing, observability — and contribute to cross-cutting standards across the wider data function
Own data quality and contracts for the data products you ship — implementing quality checks, maintaining contracts as the interface between producers and consumers, and ensuring issues are caught early and remediated cleanly
Raise the technical bar around you — through code review, design input, pairing, and the kind of senior IC presence that lifts the engineers and analysts you work with
Translate operational complexity — multiple product event sources, schema drift, ongoing integration of acquired products — into clean, durable engineering execution the business can rely on

5+ years in data engineering, with demonstrable experience operating in a senior IC capacity
Hands-on production experience with Databricks
Hands-on experience with dbt
Strong SQL and Python
Experience working with product, behavioural, or event-based data sources at scale
Track record of defining and applying engineering standards across testing, CI/CD, documentation, and observability
Experience operating in complex environments — multi-source event landscapes, high-volume pipelines, or platform migrations
Strong communication skills — credible with engineers, analysts, and senior product and business stakeholders, and able to translate technical decisions into business and product impact

Direct experience with product analytics or event-tracking platforms (e.g., Snowplow, Segment, Amplitude, Mixpanel) as data sources
Experience designing event schemas and managing schema evolution across multiple products
Familiarity with streaming or near-real-time ingestion (e.g., Kafka, Kinesis, Lakeflow)
Familiarity with the wider Databricks ecosystem — Unity Catalog, Lakeflow, MetricFlow, DQX
Experience working within a data product operating model with defined contracts and SLAs
Background in SaaS or EdTech environments
Familiarity with modern BI tools (Tableau preferred) and how data is consumed downstream

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