Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 32 days ago

Data Engineer

thinkahead145 open roles

Pay
$150,000 – $180,000 a year
Where
United States
Work mode
Remote
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowData Engineerthinkahead · United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on thinkahead's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.4%3 days
  3. 7.8%7 days
  4. 14.3%14 days
  5. 33.7%30 days
This job: posted 32 days ago

The posting

The Data Engineer, Data Platform will build and operate the data capabilities that help AHEAD teams access trusted, usable, and well-managed information. This role will develop ingestion pipelines, transformations, data models, and curated data products in the modern cloud data platform, with an emphasis on Snowflake and dbt.

The role will support data coming from enterprise applications and services, including Salesforce, Hatch, NetSuite, Signal, and approved APIs. The Data Engineer will help make data available for analytics, applications, automation, and AI-enabled workflows through consistent engineering patterns,documented definitions, appropriate access controls, and dependable operational practices. Active use of AI throughout the software development lifecycle is a core expectation of this role, including AI-assisted code generation, automated testing, documentation, troubleshooting, and review with appropriate human validation.

Working under the Director, Data Platform and alongside the Data Governance Lead, this role will contribute to a product-oriented engineering team. The role will partner with data consumers and other engineering teams to understand requirements, deliver useful platform capabilities, and improve the speed and consistency of data delivery.

Duties/Responsibilities

  • Build, maintain, and improve batch and low-latency data ingestion pipelines from enterprise systems, APIs, and other approved sources.
  • Follow the AI SDLC by actively using approved AI coding tools and agents to generate, refactor, explain, and review code; validate generated output through engineering judgment, testing, and peer review.
  • Use AI to generate and improve unit, integration, data-quality, and regression tests, then verify that automated tests accurately validate the intended behavior.
  • Use AI-assisted workflows to create and maintain technical documentation, data-product documentation, runbooks, lineage notes, and change summaries as part of delivery.
  • Build toward coordinated multi-agent delivery patterns that can divide and accelerate discovery, implementation, testing, documentation, and operational support while preserving human accountability.
  • Develop SQL and Python solutions that collect, validate, transform, and publish data for downstream consumption.
  • Use Snowflake and dbt to implement reliable transformations, reusable models, curated datasets, and data products across raw, common, and curated layers.
  • Translate business and technical requirements into source mappings, data models, acceptance criteria, and maintainable engineering solutions.
  • Partner with analytics, application, AI, Integration Platform, and business teams to make data available through governed and documented access patterns.
  • Apply data quality checks for completeness, freshness, uniqueness, consistency, referential integrity, and other relevant quality dimensions.
  • Add metadata, documentation, lineage, ownership, and usage guidance to data products so consumers can find and understand the data they use.
  • Implement secure access patterns in partnership with Data Governance and Security teams, including role-based access, classification tags, masking, and row- or column-level controls when appropriate.
  • Build automated tests and deployment processes that support consistent delivery through development, quality assurance, and production environments.
  • Monitor pipeline health, data freshness, processing performance, and failures; troubleshoot issues and participate in incident resolution.
  • Optimize Snowflake workloads, queries, transformations, and storage patterns for performance, reliability, and cost discipline.
  • Support the curation and publication of cross-system data needed for shared business context, entity-aware access, reporting, automation, and AI use cases.
  • Work with the Integration Platform and semantic-layer capabilities, including Horizon, to support consistent business meaning and reusable data access.
  • Participate in backlog refinement, estimation, code review, technical documentation, and iterative delivery within an Agile engineering team.
  • Identify opportunities to simplify delivery, reduce duplicate work, improve platform standards, and strengthen the reliability of data engineering practices.

Education and Experience

  • Bachelor’s degree in computer science, information systems, engineering, mathematics, or a related field, or equivalent experience.
  • 3 or more years of experience in data engineering, software engineering, analytics engineering, or a related technical role.
  • Professional experience writing production-quality SQL and Python.
  • Experience building or supporting data pipelines, transformations, and data models in a cloud data environment.
  • Experience with Snowflake, dbt, or comparable cloud data warehouse and transformation technologies.
  • Understanding of data modeling, ELT/ETL patterns, pipeline orchestration, APIs, and source-system integration.
  • Experience with software engineering practices including source control, code review, automated testing, and CI/CD.
  • Demonstrated active use of AI-assisted software development tools for code generation, test creation, documentation, debugging, or review.
  • Ability to follow an AI SDLC and identify practical opportunities for multiple cooperating agents to improve delivery speed, consistency, and coverage.
  • Understanding of data quality, metadata, lineage, access control, privacy, and secure handling of enterprise data.
  • Ability to investigate data issues, communicate findings clearly, and work through ambiguity with teammates and stakeholders.
  • Ability to collaborate effectively with engineers, analysts, product owners, governance partners, security teams, and business stakeholders.

Preferred

  • Experience with Azure services, serverless functions, cloud storage, or other cloud-native data engineering capabilities.
  • Experience with REST or GraphQL APIs and data ingestion from enterprise applications such as Salesforce, Hatch, NetSuite, or similar systems.
  • Familiarity with orchestration, event-driven processing, observability, data catalogs, lineage tooling, or data quality platforms.
  • Experience supporting semantic models, MCP-based access, or other governed interfaces for analytics, applications, automation, or AI workflows.
  • Experience working with master data, reference data, entity resolution, or shared business definitions across multiple systems.
  • Experience operating data products with documented ownership, access expectations, quality measures, and support procedures.
  • Experience using AI agents or agentic workflows to support software delivery, data engineering, testing, documentation, or platform operations.
  • Curiosity about emerging data platform technologies and a practical approach to adopting them.

Physical Requirements

  • Ability to safely and successfully perform the essential job functions consistent with the ADA, FMLA, and other federal, state, and local standards, including meeting qualitative and/or quantitative productivity standards.
  • Ability to maintain regular, punctual attendance consistent with the ADA, FMLA, and other federal, state, and local standards.
  • Primarily office and computer-based work with standard engineering and collaboration expectations for an enterprise technology role.
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against thinkahead's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on thinkahead's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    thinkahead's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.