[**GrayHair**](https://grayhairsoftware.com/) has spent **over 25 years** turning US postal mail into data worth its weight in gold: they process **more than 125 billion data points a year** for Fortune 500 banks, insurers and healthcare companies.
There are already several Manfred folks on the team (and they keep asking us for more, so they must be doing something right 😏). Now they're looking for a **Senior Data Analyst** who wants to rewrite their legacy with a modern stack. If you want to lead scalable technical solutions, elevate the team's working standards and raise the technical bar, this one is for you 🤩.
## What will you do?
**First, a bit of context 📬**
Before we get down to business, let's take a quick trip back in time ⏳. GrayHair was born in **2000** as a mail-tracking service. By 2008 they had a solid client base and four more services. In 2016 the company lost its founder and, far from falling apart, it reinvented itself: it stopped being "the company that tracks letters" and became **the data tech company it is today**. By 2020 the whole team was remote, with one clear goal: transform their technology from top to bottom.
So what exactly do they do? Their own motto sums it up: *Undeliverables? Unacceptable!* 📮 A letter that doesn't arrive means a credit card in the wrong mailbox, an angry customer calling the bank, or a marketing campaign straight into the bin. GrayHair exists to make sure that doesn't happen.
To pull this off, **they handle around 25% of all US postal data** and track billions of mail pieces every year. And since they work with data as sensitive as that of banks and insurers, security and engineering quality are non-negotiable.
**Their catalogue is pretty packed:**
- 📍 **GH Mail Tracking Platform:** tracks every mail piece from the moment it's sent until it arrives (or doesn't).
- 🏠 **Address quality:** tools like CASS™, 48-month NCOALink® (they're a certified Full Service Provider), VerifyAQ™ and returns management (ACS™), so their clients' databases are always clean.
- 💳 **GH Card Insights™** (launched in July 2026): turns credit and debit card delivery into useful intelligence for fraud, operations and customer experience teams.
- 📈 **GH Direct Mail IQ™:** solves one of marketing's biggest headaches, proving how much revenue direct mail really drives in an omnichannel strategy.
- ☎️ **GH Contact Center Connector™:** brings real-time postal data into call centers to cut down on "where's my letter?" calls.
It's no coincidence that *Mailing Systems Technology* magazine named them a **"Hot Company"** in 2025. And all of this runs on a lot (and we mean a lot) of software… which is exactly where you come in. 😏
**🫵 So, what's your role in all this?**
GrayHair is in the middle of a **tech transformation** centering on a Snowflake migration and Airflow pipeline orchestration hosted on AWS infrastructure.
They are looking for a **Senior Data Analytics** profile who sits at the intersection of data engineering and advanced analytics. Your mission will be to help them **elevate team working standards, raise the technical bar, and lead scalable technical solution designs**.
The team maintains over 200 data feeds across formats such as CSV, Excel, and email for hundreds of customers. They are actively migrating legacy SQL data feeds to Snowflake (a transition projected for completion within six months) while utilizing AWS infrastructure including S3 and EC2 for data uploads, downloads, and interactions. They need your help in this challenging mission 🚀.
- Oversee the **end-to-end design and execution of robust, scalable technical solutions**, ensuring system architectures are resilient, performant, and aligned with long-term business goals.
- Lead the migration of legacy **SQL data feeds to Snowflake.**
- **Build, maintain, and debug ETL data pipelines** using **Airflow** (DAG configuration, data manipulation, group-by operations, and pushing back to Snowflake).
- **Maintain and manage over 200 data feeds** (CSV, Excel, email outputs) serving hundreds of customers.
- Manage data storage and lifecycle policies in **AWS (S3 and EC2)**.
- Write stored procedures and schedule daily tasks in Snowflake.
- Implement code version control and dev standards using **Git**, **GitHub**, and **GitHub Actions**.
**The team**
You will be the 6th member of the Data & Analytics team and since you will be leading the migration **from SQL data feeds** to **Snowflake**, you will need to have experience in the field and in some particular things. To easy the tension, bear in mind that nobody expects you to lead from day one, but they do expect you to contribute once you feel confortable in your day to day.
**Required Technical Skills:**
- Strong expertise in **Snowflake and Python** (specifically Pandas).
- Strong knowledge of **query performance tuning and Snowflake/AWS cost management** (e.g., converting self-joins to window functions, managing compute resource auto-pausing).
- 🗄️ **SQL, because data is the business. SQL Server in the legacy world and PostgreSQL** in the new one: you'll move between both, with a lot of volume. Hands-on experience with SQL and Airflow (ETL pipeline orchestration).
- ☁️ **AWS**, where everything lives. **Solid working knowledge of AWS services (S3, EC2, CloudWatch)**. This isn't "push it to the cloud and forget about it": you build, deploy and keep an eye on what you own. Services run in containers on ECS, talk to each other through queues and events (SQS/SNS), use Lambda and Step Functions to orchestrate processes, sit behind API Gateway, store data in RDS/Aurora and report through CloudWatch.
- 🧪 **Quality and CI/CD. JUnit, Git/GitHub and GitHub Actions**. When you're handling data for banks and insurers, "it works on my machine" doesn't cut it. Version control proficiency with Git and GitHub / GitHub Actions.
- 💂 **Fluent English:** it's the working language 100% of the time.
**Bonus points**
- **BI Platform:** Experience with **Sigma** (or other BI platforms like Tableau, with the ability to adapt quickly).
- **Certifications:** Cloud/Data certifications such as **SnowPro** or **AWS** certifications.
And don't worry about not meeting all the requirements: nobody masters all of this 100%. If you've got the essentials and you're keen to learn the rest, apply. 😉
**Salary:** up to €65,000
- 🏖️ **23 days of holidays** + national, regional and local public holidays + **your birthday off**.
- 🌏 **100% remote** from anywhere in Spain.
- 💻 **Choose your own equipment.**
- 📚 **Training and conference budget.**
- 🤝 **Volunteer Time Off** to dedicate time to social causes.
- ✈️ **Annual offsite in the US**, all expenses paid.
- 🎉 **Team-building events and activities.**
**100% remote from Spain!**
GrayHair's HQ is in Stuart, Florida, but their culture is **remote-first**: the team is spread between the US and Spain, and what matters is results, not your zip code (and believe us, they know a thing or two about zip codes 📮).
You'll be hired in **Spain** through an EOR (a company specialized in remote hiring), with all the guarantees of Spanish employment law.
Once a year, though, the whole team gets together in **the US for a multi-day offsite**, with travel and accommodation covered. It's not mandatory, but they'll miss you if you don't go 🌴
You will join our **Data & Analytics team**, working closely with colleagues based in the US during the second half of your workday in Spain.
You’ll never fly solo here, you’ll be part of a supportive, collaborative team led by [**Janesh Devkota**](https://www.linkedin.com/in/janesh-devkota-phd-b3b60644/)**, alongside two US-based full-time engineers and two dedicated contractors** who are excited to welcome you aboard.
Oh, and you won't be alone in Spain: there are already several Manfred folks on the team, so there'll be someone to tell you what it's like to work for a US team from here 😉
Here's a photo from a recent offsite in Florida.
**Airflow serves as the primary ETL** tool for sourcing data, performing manipulations, and pushing outputs to Snowflake. **AWS CloudWatch** is used for configuring system metrics and alarms. Code version control is managed through Git, GitHub, and GitHub Actions.
That's why the team is looking for someone that has strong experience with **Snowflake and Python**, specifically utilizing the Pandas library for data manipulation and grouping.
While a separate data engineering team handles complex architecture, you are **expected to build and debug data feeds using Airflow** (covering basic configuration, DAGs, configuration retrieval, and group-by operations) without needing to construct enterprise-scale pipelines from scratch.