Data Analytics Engineer

Jobgether; United States; On-site; USD 160,000 - 190,000; Full time

Benefits offered by this job

401(k) plan

Medical and dental coverage

Total Rewards package

Bonus potential

Job summary

Jobgether, on behalf of a partner company, is seeking a Data Analytics Engineer based in the United States to build the analytics foundation and drive scalable data products.

You will architect a cloud data warehouse, own end-to-end ELT pipelines, define data models and governance, and partner with GTM, Finance, Product, and Customer Success to enable AI-powered reporting.

Qualifications

• 6+ years of analytics engineering or data engineering with ownership of production data models.
• Strong SQL expertise and a track record of delivering analytical models used by multiple teams.
• Hands-on experience with cloud data warehouses (Snowflake preferred or BigQuery).
• Extensive experience with transformation frameworks such as dbt or SQLMesh.
• Proficiency in Python or similar scripting languages for data tasks.
• Experience with BI or semantic-layer platforms like Looker, Tableau, or Omni.
• Strong governance, access controls, data quality, lineage, and security practices.
• Experience supporting AI-assisted or natural-language reporting is a plus.
• Familiarity with GTM and CS platforms (Salesforce, Gainsight, HubSpot) is advantageous.
• Experience with ML or forecasting (time-series, churn propensity) is a plus.

Responsibilities

• Architect, build, and maintain a modern cloud data warehouse for enterprise analytics.
• Own data transformations end to end from ingestion to stable analytical tables.
• Design and maintain ELT pipelines integrating GTM, Finance, Product, and Customer Success data.
• Establish BI and semantic-layer foundations, including metric definitions and data models.
• Develop curated data models supporting product usage, customer adoption, and go-to-market reporting.
• Own data quality, governance, lineage, and source-of-truth standards.
• Collaborate with stakeholders to translate measurement needs into scalable analytics solutions.
• Help establish data infrastructure for AI-powered querying and NL analytics.

Skills

SQL

Python

Analytics engineering

Data modeling

Tools

Snowflake

BigQuery

dbt

SQLMesh

Looker

Tableau

Omni

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Analytics Engineer based in United States.

This is a foundational data role focused on building the infrastructure that enables reliable, scalable business analytics.

You will architect and establish a cloud data warehouse from the ground up, creating the technical foundation for a growing analytics function.

Your work will connect data from go-to-market, finance, product, and customer success systems into a trusted source of truth.

You’ll own transformation layers, ELT pipelines, semantic models, governance, and data quality across the analytics ecosystem.

The role also offers an opportunity to shape AI-assisted reporting through a semantic layer designed for natural-language and agent-based use cases.

You’ll work closely with business stakeholders to translate measurement needs into stable, well-documented data products.

This high-visibility position combines hands-on engineering with architectural ownership and the opportunity to establish modern data practices from the ground up.

Accountabilities

• Architect, build, and maintain a modern cloud data warehouse that serves as the foundation for enterprise analytics.
• Own data transformations end to end, from raw ingestion through reliable, documented, and stable analytical tables.
• Design and maintain ELT pipelines that integrate data from GTM, Finance, Product, Customer Success, and other business systems.
• Establish the technical foundation for BI and semantic-layer capabilities, including metric definitions, data models, and access structures.
• Develop curated data models supporting product usage, customer adoption, account health, and go-to-market reporting.
• Own data quality, governance, and lineage through freshness monitoring, automated testing, access controls, documentation, and source-of-truth standards.
• Partner closely with business stakeholders to understand measurement requirements and translate them into scalable analytical solutions.
• Help establish data infrastructure that can support internal AI-powered querying, reporting, and natural-language analytics.

Requirements

• 6+ years of experience in analytics engineering, data engineering, or a related field, with demonstrated ownership of production data models.
• Strong SQL expertise and a track record of delivering analytical models relied upon by multiple teams.
• Hands-on experience with modern cloud data warehouses, with Snowflake preferred or comparable platforms such as BigQuery.
• Extensive experience with a transformation framework such as dbt or SQLMesh.
• Proficiency in Python or a similar scripting language for data ingestion, validation, automation, or related engineering tasks.
• Experience working with BI or semantic-layer platforms such as Omni, Looker, Tableau, or comparable tools.
• Strong judgment around data governance, access controls, data quality, lineage, and the responsible handling of sensitive information.
• Experience supporting AI-assisted or natural-language reporting and semantic layers designed for LLM or agent-based applications is a plus.
• Familiarity with GTM and Customer Success platforms such as Salesforce, Gainsight, or HubSpot is advantageous.
• Experience with machine learning or statistical forecasting, including time-series or churn-propensity models for metrics such as ARR and customer retention, is a plus.
• Ability to perform repetitive computer-based tasks involving wrists, hands, and fingers, and to remain seated or stationary for extended periods.

Benefits

• Estimated base salary of $160,000–$190,000 plus bonus.
• Comprehensive benefits package in addition to cash compensation.
• 401(k) plan.
• Medical and dental coverage.
• Total Rewards package with additional benefits based on eligibility.
• Compensation may vary depending on market considerations and objectively assessed individual qualifications.