Senior Analytics Engineer

toters delivery

. Design, build, and maintain scalable and modular data models using dbt within a cloud data warehouse .

Posted 9/23/2026full-timeMetn • LebanonSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data models and ELT pipelines within cloud data warehouses, with a strong focus on SQL performance and data quality governance. Proficient in mentoring teams on advanced data engineering practices and tools, ensuring efficient data architecture and deployment workflows.

Highest-signal resume keywords

Analytics EngineeringData EngineeringComplex SQL ProficiencyDbt DevelopmentCloud Data Warehousing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbtPythonData ModelingData Quality GovernanceELT PipelinesPerformance TuningAutomated TestingData ArchitectureData Exploration

Soft Skills

MentoringCollaborationProblem-Solving

Tools & Technologies

TableauGitCI/CDSnowflakeBigQueryDatabricksApache AirflowDagsterPrefectSegment

Industry Keywords

High-Growth Tech CompanyDelivery PlatformMulti-Sided MarketplaceData GovernanceData Quality

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudPythonSQLTableau

About the role

Key responsibilities & impact

Design, build, and maintain scalable and modular data models using dbt within a cloud data warehouse
Architect and optimize ELT pipelines integrating high-volume datasets across the marketplace
Champion software engineering practices within the data team, including Git, CI/CD, code reviews, and DRY code
Implement automated testing, alerting, and anomaly detection for data quality and governance
Design semantic layers and documented data marts for self-service data exploration
Audit and optimize legacy queries and warehouse compute resources
Ensure Tableau BI tools run with minimal latency
Mentor the Data Analytics team in advanced SQL, dbt modeling, and performance tuning

Requirements

What you’ll need

4+ years of experience in Analytics Engineering, Data Engineering, or a highly technical Data Analytics role
Experience ideally within a high-growth tech company, delivery platform, or multi-sided marketplace
Unmatched proficiency in writing complex, highly performant SQL
Extensive, hands-on experience building production-grade environments in dbt, including Jinja, macros, and incremental logic
Deep conceptual and practical understanding of modern columnar data warehouses, including Snowflake, BigQuery, or Databricks
Fluent in Git workflows, command-line interfaces, and setting up CI/CD workflows for data deployments
Strong proficiency in Python for API integrations, custom transformations, or pipeline scripting
Ability to translate complex operational logic into elegant data architecture
Nice to have: hands-on experience with Apache Airflow, Dagster, or Prefect
Nice to have: experience managing event-tracking pipelines such as Snowplow, Segment, or Amplitude
Nice to have: previous experience managing the semantic layer in BI platforms like Tableau