Senior Data Analytics Engineer

kore1 • United States

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Join kore1 as a Senior Data Analytics Engineer to build the data foundation that powers trustworthy reporting, self-serve insights, and decision-making across the company. This is a unique opportunity to own the core analytics engineering layer end-to-end, from defining foundational metrics and data models to implementing best practices that scale. As a senior individual contributor, you'll lead through technical ownership, influence, and execution, while helping set standards and patterns that future hires will build on.

Key Highlights

Build the data foundation that powers trustworthy reporting, self-serve insights, and decision-making

Own the core analytics engineering layer end-to-end

Partner with Product, Engineering, and GTM leaders to turn ambiguous questions into reliable, reusable data products

Key Responsibilities

Help Build the Data Foundation

Execute the analytics engineering roadmap by identifying the highest-leverage data opportunities and delivering the models and datasets needed to support them

Design and build a single source of truth by developing foundational data models (dimensional modeling, star schemas, modular marts) that standardize business definitions and metrics

Manage a modern analytics infrastructure by implementing and using tools like dbt, Snowflake, and Git, including CI/CD patterns

Implement scalable standards for modeling, naming, testing, documentation, and dataset ownership to ensure maintainability as the organization grows

Improve trust in data by implementing data quality checks, monitoring and observability practices, and clear guidance on what is trusted

Enable Self-Serve and Decision-Making

Build curated datasets and semantic-friendly layers that keep BI and reporting consistent and reliable

Create dashboards and analytics tools that empower stakeholders to self-serve confidently, with clear definitions and documentation

Translate ambiguous business questions into structured, scalable data solutions, and not one-off queries

Translate complex analytical findings into clear, actionable recommendations that influence product strategy

Lead Through Technical Ownership

Act as the analytics engineering voice in technical decisions, ensuring solutions are practical, robust, secure, and useful

Drive cross-functional projects from discovery through delivery, influencing outcomes without formal authority

Contribute to data literacy and adoption through metrics definitions, training, and strong documentation

Collaborate with product managers during discovery to identify the right problems to solve using data

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Technical Skills Required

SQL Cloud data warehouses (Snowflake) dbt Python Git GitHub CI/CD practices Data quality and reliability patterns (dbt tests, Great Expectations, Monte Carlo, alerting, SLAs) Modern data architecture patterns and tradeoffs

Benefits & Perks

Fully remote role

100% remote

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Nice to Have

Experience with semantic modeling layers like LookML

Familiarity with workflow orchestration tools (Hevo, Airflow, Dagster)

Background in high-growth startup or tech environments

Knowledge of data cataloging and metadata management tools (Atlan, etc.)

Understanding of AI/ML applications and prompt engineering for LLMs

Experience with statistical analysis and experimental design

Job Description

This is a fully remote role, however candidates must be based in U.S. Eastern Time (EST) states to align with team collaboration and working hours.

Summary:

Hiring a Data Analytics Engineer to help build the data foundation that powers trustworthy reporting, self-serve insights, and decision-making across the company. This is a unique opportunity to join at the ground floor and own the core analytics engineering layer end-to-end, from defining foundational metrics and data models to implementing best practices that scale.

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