Pay: Salary not listed in the saved posting
Work setup: Hybrid stated — work setup source
the team. Work Location: Hybrid in either Columbus, OH; Austin, TX Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time.
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Employment: Unconfirmed

Before you apply

Eligibility: Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time. — eligibility source
Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time.
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Apply at Lower, LLC

What you’ll work on

Full posting

You'll design and build major components of the data infrastructure that powers reporting, analytics,
Own complex initiatives end-to-end: define scope and a technical plan before execution, then deliver durable, scalable solutions with minimal oversight.
Support and troubleshoot business-critical pipelines and jobs in production, including incident response for the systems you own.

From the employer’s posting

who cares deeply about their craft, thinks in terms of the whole business, and holds a point of view without holding it too tightly. You'll design and build major components of the data infrastructure that powers reporting, analytics, and decision-making across the business - built on Snowflake, dbt, Looker, and Domo - while setting a high

Define modeling standards within your domain using dbt, and build curated models, marts, and reusable data assets that support reporting, analytics, operations, and executive decision-making. Own complex initiatives end-to-end: define scope and a technical plan before execution, then deliver durable, scalable solutions with minimal oversight. Solve ambiguous, multi-system technical problems from evolving requirements, and make design decisions that hold up as the business grows.

Set a high bar for code quality within your domain through thoughtful, consistent code review, drive improvements in testing, validation, and documentation practices, and keep architecture and modeling consistent across our repos. Support and troubleshoot business-critical pipelines and jobs in production, including incident response for the systems you own. Work directly with stakeholders across marketing, sales, operations, finance, product, technology, and mortgage operations - including analysts and BI teams in Looker and Domo - to translate what they need into trusted, consistent data models and metrics.

What you’ll bring

All qualifications

Core experience

5-8+ years in data engineering, analytics engineering, BI engineering, or a similar data-focused role, with demonstrated technical ownership and impact.
Deep SQL expertise and extensive experience with large, complex, and messy datasets.
Strong experience with a cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks, including performance tuning and cost optimization.
Strong Python (or similar) for data processing, automation, and pipeline orchestration.
Deep familiarity with data integration patterns: APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations.
Hands-on experience using AI-assisted development tools in real engineering work - coding, documentation, testing, code review, or automation.

Qualification wording

5-8+ years in data engineering, analytics engineering, BI engineering, or a similar data-focused role, with demonstrated technical ownership and impact.

Deep SQL expertise and extensive experience with large, complex, and messy datasets.

Strong experience with a cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks, including performance tuning and cost optimization.

Strong Python (or similar) for data processing, automation, and pipeline orchestration.

Deep familiarity with data integration patterns: APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations.

Hands-on experience using AI-assisted development tools in real engineering work - coding, documentation, testing, code review, or automation.

Tools in this posting

Python
SQL
BigQuery
Databricks
dbt
Looker
Redshift
Snowflake
Tableau
Power BI

Source

- Substantial experience with dbt or a similar transformation framework, including designing reusable patterns and standards. - Strong Python (or similar) for data processing, automation, and pipeline orchestration. - Deep familiarity with data integration patterns: APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations.

- 5-8+ years in data engineering, analytics engineering, BI engineering, or a similar data-focused role, with demonstrated technical ownership and impact. - Deep SQL expertise and extensive experience with large, complex, and messy datasets. - A track record of designing and owning production pipelines and data models that other people built on top of - not just building to spec.

- A track record of designing and owning production pipelines and data models that other people built on top of - not just building to spec. - Strong experience with a cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks, including performance tuning and cost optimization. - Substantial experience with dbt or a similar transformation framework, including designing reusable patterns and standards.

it too tightly. You'll design and build major components of the data infrastructure that powers reporting, analytics, and decision-making across the business - built on Snowflake, dbt, Looker, and Domo - while setting a high engineering bar within your domain and mentoring the engineers around you.

- Lead the ingestion of our most complex datasets into the core schema, across a wide variety of source systems, connectors, data shares, SFTP transfers, APIs, and native integrations. - Define modeling standards within your domain using dbt, and build curated models, marts, and reusable data assets that support reporting, analytics, operations, and executive decision-making. - Own complex initiatives end-to-end: define scope and a technical plan before execution, then deliver durable, scalable solutions with minimal oversight.

- Strong experience with a cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks, including performance tuning and cost optimization. - Substantial experience with dbt or a similar transformation framework, including designing reusable patterns and standards. - Strong Python (or similar) for data processing, automation, and pipeline orchestration.

- Mortgage, lending, financial services, real estate, or fintech. - Hands-on Snowflake, dbt, Looker, and/or Domo at scale. - Claude Code, Cursor, GitHub Copilot, or similar AI-assisted development tools.

- Deep familiarity with data integration patterns: APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations. - Fluency with BI and analytics tools such as Looker, Domo, Tableau, or Power BI, including semantic layer design. - Hands-on experience using AI-assisted development tools in real engineering work - coding, documentation, testing, code review, or automation.

What you’ll do: - Design and build major components of our warehouse in Snowflake - ingestion layer, transformation layer, and core schema domains - including work in legacy Redshift environments as we modernize. - Lead the ingestion of our most complex datasets into the core schema, across a wide variety of source systems, connectors, data shares, SFTP transfers, APIs, and native integrations.

Job description

View original posting ↗

Job Description:

Lower.com is looking for a Senior Data Engineer to join our Data & Analytics team. We're looking for someone

who cares deeply about their craft, thinks in terms of the whole business, and holds a point of view without holding

it too tightly. You'll design and build major components of the data infrastructure that powers reporting, analytics,

and decision-making across the business - built on Snowflake, dbt, Looker, and Domo - while setting a high

engineering bar within your domain and mentoring the engineers around you.

This role carries real ownership. You'll take complex initiatives from scoping through delivery with minimal

oversight, and you'll spot problems in data quality, architecture, or process before they're handed to you.

We're also investing in modern AI development tools and agentic workflows, including Claude Code and Cursor.

We're looking for someone who already uses these tools in their daily work and is glad to share what's working with

the team.

Work Location: Hybrid in either Columbus, OH; Austin, TX

Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time.

What you’ll do:

Design and build major components of our warehouse in Snowflake - ingestion layer, transformation layer, and core schema domains - including work in legacy Redshift environments as we modernize.
Lead the ingestion of our most complex datasets into the core schema, across a wide variety of source systems, connectors, data shares, SFTP transfers, APIs, and native integrations.
Define modeling standards within your domain using dbt, and build curated models, marts, and reusable data assets that support reporting, analytics, operations, and executive decision-making.
Own complex initiatives end-to-end: define scope and a technical plan before execution, then deliver durable, scalable solutions with minimal oversight.
Solve ambiguous, multi-system technical problems from evolving requirements, and make design decisions that hold up as the business grows.
Anticipate scalability constraints and downstream impacts, identify re-architecture needs proactively, and propose the fix.
Set a high bar for code quality within your domain through thoughtful, consistent code review, drive improvements in testing, validation, and documentation practices, and keep architecture and modeling consistent across our repos.
Support and troubleshoot business-critical pipelines and jobs in production, including incident response for the systems you own.
Work directly with stakeholders across marketing, sales, operations, finance, product, technology, and mortgage operations - including analysts and BI teams in Looker and Domo - to translate what they need into trusted, consistent data models and metrics.
Mentor junior and mid-level engineers through code review, pairing, and technical guidance, and influence modeling and architecture decisions within the team.

Who you are:

High give a sh*t factor - You care about the quality of what you deliver, holding yourself to a high standard - and you do your best work alongside people who do the same.
Same team, same mission - You collaborate generously and treat teammates and stakeholders as partners, not requesters. Everyone here is working toward the same ambition.
A problem-solver at heart - You're drawn to hard, ambiguous challenges, and you're motivated by building solutions the business actually feels.
Strong opinions, loosely held - You bring a real point of view and make the case for it - in a doc, a code review, or a room - and you update when the evidence says to. You care more about getting it right than being right.
5-8+ years in data engineering, analytics engineering, BI engineering, or a similar data-focused role, with demonstrated technical ownership and impact.
Deep SQL expertise and extensive experience with large, complex, and messy datasets.
A track record of designing and owning production pipelines and data models that other people built on top of - not just building to spec.
Strong experience with a cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks, including performance tuning and cost optimization.
Substantial experience with dbt or a similar transformation framework, including designing reusable patterns and standards.
Strong Python (or similar) for data processing, automation, and pipeline orchestration.
Deep familiarity with data integration patterns: APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations.
Fluency with BI and analytics tools such as Looker, Domo, Tableau, or Power BI, including semantic layer design.
Hands-on experience using AI-assisted development tools in real engineering work - coding, documentation, testing, code review, or automation.
Comfort operating with limited direction: scoping your own work, sequencing it, and knowing when to pull others in.
Experience mentoring or informally leading other engineers.
Ability to communicate clearly with both technical and non-technical stakeholders, including leadership.

Preferred Experience:

Mortgage, lending, financial services, real estate, or fintech.
Hands-on Snowflake, dbt, Looker, and/or Domo at scale.
Claude Code, Cursor, GitHub Copilot, or similar AI-assisted development tools.
Building with AI agents, workflow automation, or LLM-powered internal tools.
Orchestration tools, cloud platforms, CI/CD, or modern data stack tooling.
Designing data governance, data quality testing, or observability frameworks rather than following existing ones.
Supporting executive reporting, operational analytics, marketing analytics, mortgage operations, or sales funnel reporting.
Leading technical design reviews.

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Source & posting history

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Source excerpts

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Pay: No pay amount identified in the saved description.
Location & working pattern: Austin, TX 78702
the team. Work Location: Hybrid in either Columbus, OH; Austin, TX Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time.
Work authorization: Work Location: Hybrid in either Columbus, OH; Austin, TX Work Type: Full-time W2 employment, visa sponsorship is not available for this position at this time. What you’ll do:

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