Data Platform Lead

Remote (US East Coast / Eastern Time Zone Preferred), Eastern Time Zone PreferredFull-TimeLead

SalaryBase Salary Range: $180,000 – $200,000; Total Target Compensation: $198,000 – $220,000 (includes base salary + annual incentive performance bonus)

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Job Details

Experience: 7+ years in data engineering, analytics engineering or data architecture
Required Skills: SnowflakeTerraformData modelingdbt

Requirements

Have 7+ years in data engineering, analytics engineering, or data architecture.
Have built a modern data platform that people rely on in production.
Use AI agents for real multi-step work such as building models, writing tests, debugging pipelines, and documenting systems; verify their output against the real system.
Have deep experience with dbt and Snowflake, including project structure, testing strategy, and warehouse performance at scale.
Have managed a platform as code with Terraform or a similar tool.
Be fluent in data modeling and have moved a team from source-shaped models to business-shaped, domain-oriented marts and adoption.
Have built data quality and observability practices, including tests, contracts, freshness monitoring, and alerting.
Have built a semantic layer and governed metrics, and understand accurate natural-language and agent-driven analytics.
Have worked with managed ingestion such as Fivetran.
Have led beyond individual work through a tech lead role, mentoring, interview loops, or directing contractors or vendors.
Explain modeling decisions and metric definitions clearly to engineers and non-engineers.
Set direction, make architecture decisions, and document reasoning independently.

Responsibilities

Own data platform architecture, reliability, and roadmap across Snowflake, dbt, and Fivetran.
Move platform configuration into Terraform so warehouses, roles, grants, and connectors are versioned, reviewed, and reproducible.
Set modeling standards, naming conventions, and review practices for domain-oriented business models.
Partner with Finance, Sales, Operations, and venue leadership to turn business questions into trusted models, metrics, and definitions.
Work with product squads on schema design, data contracts, and upstream changes.
Set data quality testing, contracts, reconciliation checks, freshness monitoring, and alerting practices.
Roll out the BI tool and build a semantic layer with governed dashboards, certified metrics, and shared definitions.
Stand up natural-language querying and agents on Snowflake tools, with evaluations and guardrails.
Manage and hire analytics engineers, direct contractors, and coach through code review and pairing.
Write dbt models, review pull requests, debug pipelines, and prototype new approaches.

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