Contractor: Lead Analytics Engineer

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Data EngineerData

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Requirements Summary

8+ years of professional experience working with data in a software engineering environment. Mastery of SQL and Python,

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Data EngineerData

This role provides technical leadership for a modern analytics engineering function, shaping the architecture, standards, and practices that support data-driven decision-making.
You will build and govern scalable data models, semantic layers, and reliable analytics infrastructure.
The position combines hands-on engineering with technical direction, mentoring, and cross-functional partnership.
You will work closely with Product, Finance, Marketing, and Engineering to translate business needs into an actionable data roadmap.
A strong focus on testing, automation, monitoring, and operational excellence will help ensure trusted and maintainable data systems.
You will also lead large-scale migrations and performance initiatives while enabling the broader team to execute effectively.
This is an opportunity to influence the technical direction of an analytics organization while turning complex data into reliable, actionable insights.

Set the technical direction for the analytics team, including architecture, engineering conventions, and development approaches.
Raise engineering standards through code reviews, design reviews, pairing, and consistent quality expectations.
Own the architecture of data models with a focus on long-term maintainability, scalability, and reliability.
Govern the semantic layer, metric definitions, and self-service analytics capabilities to help stakeholders access accurate information.
Serve as the primary technical partner to Product, Finance, Marketing, and Engineering, translating business needs into an executable roadmap.
Collaborate directly with stakeholders to negotiate scope, priorities, and delivery expectations.
Establish a proactive analytics cadence that identifies important business questions and opportunities beyond incoming requests.
Define the data testing strategy and ensure business logic is consistently validated across the analytics layer.
Own the operational health of analytics systems, including monitoring, alerting, incident response, and release readiness.
Mentor engineers, facilitate knowledge sharing, and build technical alignment through documentation and presentations.
Lead large-scale data migrations and performance initiatives by setting the technical approach and enabling the team to execute successfully.

Requirements

~1 min read

8+ years of professional experience working with data in a software engineering environment.
Mastery of SQL and Python, with strong hands-on experience applying both to analytics engineering and data systems.
Advanced experience with semantic layer tooling, data catalog platforms, and data integrity testing frameworks.
Strong experience with dbt orchestration, development standards, and analytics engineering best practices.
Proven ability to work autonomously and proactively, with deep expertise in data analysis and data systems.
Experience with relational databases and DAG orchestration tools such as Dagster or Airflow.
Hands-on experience with Tableau and modern analytics workflows.
Experience with cloud infrastructure such as AWS or GCP, as well as infrastructure-as-code tools such as Terraform.
Familiarity with document, graph, or schema-less data stores.
Strong technical leadership and mentoring capabilities, with the ability to establish engineering standards and raise team-wide quality.
Excellent stakeholder communication and collaboration skills, including the ability to translate complex technical concepts into practical business outcomes.