Principal Data Engineer (Product Data)

About the role

Everway is a growing EdTech SaaS business with a complex, multi-product data landscape. Our product data — the telemetry, usage, and engagement signals generated across our learning products — is how we understand what learners actually do, what works, and where we move the needle on outcomes. As our product portfolio grows through development and acquisition, the engineering work behind this data is becoming more complex, not less.

We're looking for a Principal Data Engineer to bring permanent senior engineering depth into this domain. You'll be a hands-on senior IC, leading the design and delivery of product data products on our Databricks lakehouse — from high-volume event ingestion through to governed, contract-backed datasets consumed by analytics, product management, and downstream AI use cases. You'll take on the hardest problems in the domain: event schema governance, identity resolution across products, sessionisation, and modelling product usage through to learner outcomes.

This role reports to the VP of Product Data and sits within the wider Data Engineering function. You'll contribute to the engineering standards that shape how the data team builds and operates. This is a senior IC role with deep technical authority and standards influence.

Main responsibilities

• 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

Essential Criteria

• 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

Desirable Criteria

• 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

Please submit your application by Friday 10th July 2026.

Please note: applications may close early due to high demand, so early submission is encouraged.