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Senior Data Engineer (Remote)

Zencastr· Data Analytics
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RemoteFull-timePosted 1mo ago

About the role

As the first dedicated Data Engineer, you’ll build and own the data foundation powering analytics, reporting, and decision-making. Design a conformed dimensional model, own end-to-end pipelines, establish data practice standards, and implement identity resolution to connect entities across systems.

Responsibilities

  • Design and build a conformed, Kimball-style dimensional model across operational, behavioral, and transactional data
  • Own ingestion end to end, including capturing change over time from sources that don't preserve history natively
  • Consolidate transformation logic that currently lives in more than one place into a single governed, tested layer
  • Implement and manage our data warehouse and transformation layer, taking ownership of the pipelines that move data from our operational systems into it
  • Establish foundational best practices for data modeling, documentation, testing, and governance
  • Improve data reliability, quality, and accessibility across systems
  • Collaborate with analysts and business stakeholders to support evolving data needs
  • Encode business metric definitions once, so that reporting stops drifting across teams
  • Monitor and optimize performance and cost efficiency across pipelines, storage, and warehouse queries

Qualifications

  • 5+ years of experience specifically in data engineering, analytics engineering, or a closely related role, including having built and owned a dimensional model in production
  • Strong proficiency in SQL, with experience across document-based operational databases (e.g., MongoDB) and analytical data warehouses (e.g., BigQuery, Snowflake, Redshift, or similar)
  • Experience building fact and dimension tables using star schema principles to support reporting and data marts, with a clear point of view on grain, conformed dimensions, and slowly-changing dimensions
  • Hands-on experience with modern transformation and modeling frameworks (e.g., dbt, Dataform, or similar), including managing transformation layers within a warehouse environment with version control, testing, and CI
  • Built and maintained reliable ETL/ELT pipelines that transform raw application data into structured, analytics-ready datasets
  • Worked with orchestration tooling (e.g., Airflow, Dagster, Prefect, or similar) and think in terms of dependencies, retries, and backfills
  • Experience with data ingestion or event streaming platforms (e.g., RudderStack, Segment, Pub/Sub, or similar) and ensuring consistent, reliable upstream data flows, including identity stitching across web and mobile
  • Solid understanding of data modeling best practices, including schema design, dimensional modeling, and performance considerations
  • Track record of inheriting and operating systems you didn't build
  • Strong focus on data quality, validation, and governance, with ability to identify and resolve inconsistencies
  • Understanding of performance optimization across pipelines, storage, and warehouse queries
  • Ability to explain technical tradeoffs clearly to non-engineers
  • Comfort operating in a growing environment where you both execute technically and help shape our data architecture standards

Skills

Required:SQLDimensional modelingdbt or DataformETL/ELT pipelinesOrchestration toolsData ingestion / streaming
Last updated Sep 17, 2026. Interested? Apply on the company site.

About Zencastr

Built for quality. Designed for growth. A new era for creation is here.

The only complete audio + video platform to get best-in-class recording, intuitive editing, AI-powered growth features, and top-tier distribution tools — all in one place.

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