Palmetto Clean Technology

Staff Data Engineer

Remote - United States

Actively hiring, first seen by us 7 days ago

Pay: Pay not listedSimilar roles state $127K–$190K
Work setting: Remote — work setting source
Location This position will be remote based in the United States. Reporting
Listed location: Remote - United States
Read the full posting
Employment: Not stated

What you’ll work on

Full posting

Build and own data products from bronze to gold for analysts, product teams and AI tools
Shape semantic context and interfaces so agents answer from governed definitions
Treat classification, masking and access policy as code; prepare for SOC 2 audits
Operate ingestion and orchestration pipelines with CI/CD, observability and SLAs
Design and run the secure, low-latency interface that products, partners and agents use

From the employer’s posting

Build and own data products that deliver trustworthy data, from bronze to gold

Shape the semantic context, documentation, and interfaces that let agents answer from governed definitions

Treat classification, masking, access policy, and change control as code, and prepare the platform for SOC 2 and related compliance audits.

Operate ingestion and orchestration as code, with CI/CD, observability, alerting, and SLAs.

Design and operate the secure, authorized, low-latency interface through which products, partners, and agents consume data.

What you’ll bring

All qualifications

Core experience

8+ years in data engineering, including time at a Staff or lead level owning a platform used by multiple teams.
Deep experience in SQL and Python.
Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform).
Experience with ETL orchestration (e.g., Fivetran, Airflow).

Preferred experience

Knowledge of reporting tools such as Looker and Hex is a plus

Qualification wording

8+ years in data engineering, including time at a Staff or lead level owning a platform used by multiple teams.

Deep experience in SQL and Python.

Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform).

Experience with ETL orchestration (e.g., Fivetran, Airflow).

Knowledge of reporting tools such as Looker and Hex is a plus

Apply at Palmetto Clean Technology

Posting record

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Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Oct 28, 20267 days ago
Recorded sightings: 8
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 7

Similar jobs usually come down between day 5 and day 54.

From 10,704 similar postings that came down. Coming down is not always a hire.

Palmetto Clean Technology is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Takes jobs down quickly

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
Azure
BigQuery
dbt
Fivetran
GCP
Looker
Snowflake
Airflow

Where the posting names them

- 8+ years in data engineering, including time at a Staff or lead level owning a platform used by multiple teams. - Deep experience in SQL and Python. - Strong database fundamentals in a modern analytical warehouse (e.g., Snowflake, BigQuery): schema design, query plans, distributed computing.

- Experience with ETL orchestration (e.g., Fivetran, Airflow). - Infrastructure as code and container orchestration on a major cloud (AWS, GCP, or Azure). - Demonstrated agentic engineering beyond prompting: you run coding agents in loops checked by specs and tests, and stay curious about new tools.

- Deep experience in SQL and Python. - Strong database fundamentals in a modern analytical warehouse (e.g., Snowflake, BigQuery): schema design, query plans, distributed computing. - Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform).

- Strong database fundamentals in a modern analytical warehouse (e.g., Snowflake, BigQuery): schema design, query plans, distributed computing. - Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform). - Experience with ETL orchestration (e.g., Fivetran, Airflow).

- Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform). - Experience with ETL orchestration (e.g., Fivetran, Airflow). - Infrastructure as code and container orchestration on a major cloud (AWS, GCP, or Azure).

- Working knowledge of API design, authentication and authorization (e.g., OAuth/OIDC, RBAC), and PII handling. - Knowledge of reporting tools such as Looker and Hex is a plus Employment is contingent upon the successful completion of a background check.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Company Description

Palmetto is a consumer energy platform that provides homeowners with a single destination to discover, purchase, finance, install, monitor and manage home energy products and services. By offering one integrated platform across solar, battery storage, HVAC, heat pumps and more, Palmetto helps homeowners make home energy more affordable, reliable and accessible. Today Palmetto serves hundreds of thousands of homeowners, across 30+ states, building the operating infrastructure for the consumer energy transition, one home at a time.

Our employees are our most valuable resource. We foster a promote-from-within culture that prioritizes talent development, career growth, and purpose-driven work. Palmetto offers a comprehensive benefits package—including unlimited PTO, medical, dental, and vision coverage, paid parental leave, retirement plans, and more—so you can have it all both personally and professionally. Palmetto prioritizes people, planet, and profit—backed by a culture that values collaboration, impact, and balance. Join us in building a brighter, cleaner world.

Location

This position will be remote based in the United States.

Reporting

This position will report to the Senior Manager, Data Engineering.

Summary of Role

You will own the technical design of the data platform that powers Palmetto's products, partners, and AI agents. Our data spans the whole customer journey: sales, lending, installation, interconnection, and years of system production. You will turn it into one governed, trustworthy view of the business, with each metric defined once so every dashboard, notebook, and agent returns the same answer. You will also build the secure, authorized, auditable path that lets people and systems use that data directly.

This is a high-leverage individual-contributor role. You'll set technical direction, write foundational code, and work closely with core platform and product teams. AI agents are first-class consumers of our platform, and we build with them every day.

Strategic & Tactical

Model the business. Build and own data products that deliver trustworthy data, from bronze to gold, for analysts, engineers, product teams, partners, and AI tools.
Make data agent-ready. Shape the semantic context, documentation, and interfaces that let agents answer from governed definitions, with answers that trace back to source.
Build governance in. Treat classification, masking, access policy, and change control as code, and prepare the platform for SOC 2 and related compliance audits.
Build and run pipelines. Operate ingestion and orchestration as code, with CI/CD, observability, alerting, and SLAs.
Communicate. Partner with finance, operations, product and engineering to understand how their data requirements are evolving.
Build the access path. Design and operate the secure, authorized, low-latency interface through which products, partners, and agents consume data.
Raise the bar. Review code, mentor teammates, and give engineering teams templates and CI checks to ship trusted data.

Qualifications

8+ years in data engineering, including time at a Staff or lead level owning a platform used by multiple teams.
Deep experience in SQL and Python.
Strong database fundamentals in a modern analytical warehouse (e.g., Snowflake, BigQuery): schema design, query plans, distributed computing.
Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform).
Experience with ETL orchestration (e.g., Fivetran, Airflow).
Infrastructure as code and container orchestration on a major cloud (AWS, GCP, or Azure).
Demonstrated agentic engineering beyond prompting: you run coding agents in loops checked by specs and tests, and stay curious about new tools.
Design docs that settled cross-team architecture questions, and clear written and verbal communication with non-technical partners.
Working knowledge of API design, authentication and authorization (e.g., OAuth/OIDC, RBAC), and PII handling.
Knowledge of reporting tools such as Looker and Hex is a plus

Employment is contingent upon the successful completion of a background check.

Equal Employment Opportunity

Palmetto embraces diversity and is an Equal Employment Opportunity employer. Employment is decided on the basis of qualifications, merit, and business need. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or any other status protected under federal, state, or local law.

To ensure a fair evaluation, we may use AI to assist in sorting applications, but all final decisions are made by our hiring team and no candidate dispositions are automated. We will keep your information on file for four years from the date of your application. For detailed information about how we handle your data and our use of AI, please review our full privacy policy.

For more about our Privacy Policy, visit: https://palmetto.com/privacy-policy

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