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

Open nowPosted 4 hours agoWe saw it 110 min after it went up

Analytics Engineer

DoiT54 open roles

Where
Remote LATAM
Work mode
Remote
Get the CV for this job

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

Your applicationOpen nowAnalytics EngineerDoiT · Remote LATAM

  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 DoiT'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.

12.3% of postings close within 7 days. Measured by our own scanner across the market. DoiT postings stay open a median of 27 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted 4 hours ago

DoiT median: 27 days open

The posting

Location As an Analytics Engineer, you will join the Business Intelligence team within Business Systems Engineering, a group of several teams that builds and runs the systems the company operates on. This role is based remotely in Mexico or Colombia as a full-time employee or in other LATAM locations as a contractor, with working hours that overlap meaningfully with US time zones.

Who We Are DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state - from planning to production.

Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency.

With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide.

The Opportunity

Our governed data platform is a core part of how DoiT operates, with hundreds of Do’ers relying on it every month. We are growing the team that builds and runs it, and we’re looking for an Analytics Engineer to help carry it forward.

You will work as an engineer on the data platform, not just a builder of reports. You are the kind of person who is averse to doing the same manual task twice, who treats data models like production code, and who instinctively adds tests and monitoring so problems are caught before anyone else sees them. You will own a meaningful share of the platform’s day-to-day engineering, which lets our analysts stay focused on analysis and lets our larger platform initiatives get the sustained attention they need.

This is a high-ownership role with real room to grow. You will work closely with our BI analysts and engineers and with partners across the business, reporting to the Head of Business Intelligence.

Responsibilities

  • Shared ownership of the platform's engineering: routine model changes, the engineering backlog, new data source onboarding from raw ingestion to certified datasets, CI/CD maintenance, and infrastructure operations. This is a full-ownership role, not a narrow lane.
  • Build, test, and maintain data models and pipelines that power dashboards, finance and investor reporting, and our AI analytics layer, across 15+ business domains including Finance, Sales, Customer Experience, Marketing, Product, and HR.
  • Manage data infrastructure as code. Provision and configure BigQuery datasets, views, GCS buckets, and IAM permissions through Terraform. This includes onboarding ingestion destinations, managing access controls, and handling schema drift on source tables.
  • Own data access and governance. Own and continue expanding our RBAC implementation — extend the access control framework as new domains and consumers come online, keep data catalog metadata (tier, domain, owner, PII tags) current, and keep documentation up to date.
  • Improve platform reliability by strengthening testing standards, observability, and alerting, so issues are caught early rather than reported by users.
  • Support orchestration and scheduling. Understand how Airflow DAGs run dbt builds (daily, hourly, monthly), tag models so they land in the right schedule, and troubleshoot build failures in Cloud Composer.
  • Build and maintain custom data connectors. When a SaaS source isn't covered by a native Fivetran connector, write and maintain Python-based Fivetran SDK connectors — including pagination, rate limiting, error handling, and automated tests.
  • Partner with BI analysts to turn ambiguous questions into well-modeled, trustworthy datasets, and help raise the team's engineering practices through code review and shared standards.
  • Use modern AI tooling to draft code and accelerate routine work, amplifying your output rather than adding manual effort.

Qualifications

  • Analytics engineering experience. 3–5 years in analytics engineering, data engineering, or BI engineering, with a track record of delivering data models that other people depend on.
  • Strong SQL and data modeling. You write, read, and optimize complex analytical queries, reason about grain and joins, and design clean, layered models with sound judgment about where logic belongs (staging, business logic, consumption layer).
  • dbt / Data transformation proficiency. You've built and maintained dbt projects professionally — packages, macros, incremental strategies, snapshots, seeds, and CI/CD. You've implemented staging → intermediate → mart patterns and understand deferred builds, state comparison, and slim CI.
  • Software engineering discipline. Version control, code review, automated testing, and CI/CD, with the habit of making changes safe to ship. You have a strong drive to automate repetitive manual work.
  • Pipeline reliability instincts. You debug data issues to their root cause, and you think about freshness, volume, duplicates, and late-arriving data before they become incidents.
  • Business translation. You translate business needs into data requirements, work with non-technical stakeholders (including Finance), and push back constructively when a request is better solved a different way.
  • Multi-repo comfort. Our data platform spans several repositories (transformation, data infrastructure, orchestration, custom connectors, foundational cloud resources). You're comfortable navigating across these boundaries rather than treating dbt as the whole world.
  • AI-assisted development. Proven track record of using AI coding tools in your daily workflow.
  • Remote ownership. Independence in a remote, global team, with clear written communication and the discipline to document your work.
  • Fluent English. Both written and spoken; knowledge of any other language is an advantage.

Bonus Points

  • Our stack. Hands-on experience with Google BigQuery, Fivetran, and Apache Airflow (Cloud Composer); or an AWS/Azure equivalent.
  • Data catalog and governance tooling. Experience with a data catalog (for example OpenMetadata) or data observability tooling (for example Elementary).
  • Git-based CI/CD for data. Experience with CI/CD workflows for data projects — branch-based deployments, slim CI, Docker image builds, and automated plan/apply cycles.
  • Terraform for data infrastructure. You've provisioned BigQuery datasets, IAM bindings, or GCS buckets with Terraform.
  • Python for data integration. You've written Python that talks to REST APIs — pagination, rate limiting, error handling.
  • dbt build lifecycle fluency. You understand how dbt compiles Jinja into SQL, how run/test/snapshot phases chain together, and you've written macros beyond basic ref() and source().
  • BigQuery performance tuning. Experience with partitioning, clustering, incremental strategies, and reasoning about slot consumption and query costs for large datasets.
  • Docker and Kubernetes. Our dbt builds run in containers on GKE. Experience with Docker images and basic Kubernetes concepts (pods, logs, deployments) helps when debugging pipeline issues.
  • Pre-commit hooks and code quality automation. Experience with SQLFluff, pre-commit frameworks, or custom validation scripts.
  • SaaS source system familiarity. Prior experience modeling data from CRM, support, project management, marketing automation, or ERP platforms.

Are you a Do’er? Be your truest self. Work on your terms. Make a difference.

We are home to a global team of incredible talent who work remotely and have the flexibility to have a schedule that balances your work and home life. We embrace and support leveling up your skills professionally and personally.

What does being a Do’er mean? We’re all about being entrepreneurial, pursuing knowledge, and having fun! Click here to learn more about our core values.

Sounds too good to be true? Check out our Glassdoor Page.

We thought so too, but we’re here and happy we hit that ‘apply’ button.

Full-time employee benefits include:

  • Unlimited Vacation
  • Flexible Working Options
  • Health Insurance
  • Parental Leave
  • Employee Stock Option Plan
  • Home Office Allowance
  • Professional Development Stipend
  • Peer Recognition Program

Many Do’ers, One Team DoiT unites as Many Do’ers, One Team, where diversity is more than a goal - it’s our strength. We actively cultivate an inclusive, equitable workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.

#LI-Remote

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 DoiT'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 DoiT'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

    DoiT'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.