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Cairo, Egypt
Live, first seen by us 32 days agoEmployment type in the employer’s posting: FullTimeFrom the employer’s posting
Develop and maintain the data warehouse and analytics-ready datasets
Own and evolve the dbt codebase with testing and documentation standards
Integrate third-party data sources such as HubSpot, GitHub and Linear
Build data models that support self-serve analytics with analysts and stakeholders
Build tooling that improves the development experience for analytics users
Develop and maintain our data warehouse and curated, analytics-ready datasets used across the company.
Own and evolve our dbt codebase, applying best practices in modularity, testing, and documentation.
Integrate 3rd party data sources (e.g. HubSpot, GitHub, Linear) into our data ecosystem
Partner with analysts and stakeholders to design and implement scalable data models that support self-serve analytics.
Build and maintain tooling and infrastructure to improve the development experience (DevX) of our analytics and business users.
Proven experience in analytics or data engineering roles, with a strong focus on enabling downstream analytics and reporting.
Strong proficiency in Python for scripting, tooling, and data transformation tasks.
Hands-on experience with dbt and SQL-based data transformation pipelines.
Deep understanding of data modeling principles (e.g. dimensional modeling, star/snowflake schema).
Familiarity with modern OLAP data warehouses like Snowflake (preferred), BigQuery, or Redshift.
Experience working with orchestration tools such as Airflow or similar.
Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes is a plus).
From the employer’s posting.
We are backed by some of the world’s top investors including Andreessen Horowitz, HV Capital, EQT Ventures and General Catalyst, who share our mission to simplify payment complexity globally.
In the employer’s words · Read in context
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 32
Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
1 open job
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Hiring recordAdd 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.
- Proven experience in analytics or data engineering roles, with a strong focus on enabling downstream analytics and reporting. - Strong proficiency in Python for scripting, tooling, and data transformation tasks. - Hands-on experience with dbt and SQL-based data transformation pipelines.
- Strong proficiency in Python for scripting, tooling, and data transformation tasks. - Hands-on experience with dbt and SQL-based data transformation pipelines. - Deep understanding of data modeling principles (e.g. dimensional modeling, star/snowflake schema).
- Experience working with orchestration tools such as Airflow or similar. - Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes is a plus). - Excellent communication skills and the ability to work cross-functionally with technical and non-technical stakeholders.
- Deep understanding of data modeling principles (e.g. dimensional modeling, star/snowflake schema). - Familiarity with modern OLAP data warehouses like Snowflake (preferred), BigQuery, or Redshift. - Experience working with orchestration tools such as Airflow or similar.
- Develop and maintain our data warehouse and curated, analytics-ready datasets used across the company. - Own and evolve our dbt codebase, applying best practices in modularity, testing, and documentation. - Integrate 3rd party data sources (e.g. HubSpot, GitHub, Linear) into our data ecosystem to enrich reporting and analytics.
- Familiarity with modern OLAP data warehouses like Snowflake (preferred), BigQuery, or Redshift. - Experience working with orchestration tools such as Airflow or similar. - Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes is a plus).
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Payrails is a global payment software company helping leading enterprises to take control of their payment operations and maximize performance. With deep experience in the payments space and firsthand knowledge of merchants' challenges, we’ve seen how fragmented, complex, and inefficient these systems can become. Now, we are setting a new industry standard for how enterprises around the world manage and optimize payments, with more control, visibility and flexibility than ever before.
Our vision is to reimagine payments from the ground up. We are building a deeply integrated meta layer that spans the entire payment lifecycle with a modular architecture. This helps us give leading brands building blocks to craft solutions to most complex operational challenges, tailor seamless customer experiences and grow their business.
We are backed by some of the world’s top investors including Andreessen Horowitz, HV Capital, EQT Ventures and General Catalyst, who share our mission to simplify payment complexity globally.
At Payrails, we’re committed to building a team of exceptional people - not just talented, but driven to build, solve, and deliver at the highest level. Excellence isn’t just a value here; it’s a way of working. We believe that great people thrive in environments where there’s trust, clarity, and shared purpose. We work openly and collaboratively, with deep respect for each other’s craft. Everyone is encouraged to understand the bigger picture - what we’re building, why it matters, and what stands in the way. When people have that context, they move faster, take ownership, and make better decisions. We care about creating a culture where people feel inspired to do their best work and a deep sense of responsibility to help us bring our vision to life. Success at Payrails means staying focused on the problems that matter most, and executing with purpose.
Your teamAt Payrails, data is at the core of everything we do. We don’t just analyze data; we turn it into actionable insights that fuel smarter decision-making and drive the future of our products. As we continue to revolutionize the payments industry we are seeking an exceptional Senior Analytics Engineer to help us in our mission.
Our tech team offers you the chance to work alongside a group of highly ambitious and knowledgeable Engineers, while being faced with complex problems that affect customers on a global scale.
How you will make an impactDevelop and maintain our data warehouse and curated, analytics-ready datasets used across the company.
Own and evolve our dbt codebase, applying best practices in modularity, testing, and documentation.
Integrate 3rd party data sources (e.g. HubSpot, GitHub, Linear) into our data ecosystem to enrich reporting and analytics.
Build and maintain tooling and infrastructure to improve the development experience (DevX) of our analytics and business users.
Partner with analysts and stakeholders to design and implement scalable data models that support self-serve analytics.
Advocate for data engineering and analytics best practices, ensuring a culture of data trust, documentation, and reproducibility.
Champion data democratization — ensuring teams have the right tools and trusted data to make informed decisions.
Proven experience in analytics or data engineering roles, with a strong focus on enabling downstream analytics and reporting.
Strong proficiency in Python for scripting, tooling, and data transformation tasks.
Hands-on experience with dbt and SQL-based data transformation pipelines.
Deep understanding of data modeling principles (e.g. dimensional modeling, star/snowflake schema).
Familiarity with modern OLAP data warehouses like Snowflake (preferred), BigQuery, or Redshift.
Experience working with orchestration tools such as Airflow or similar.
Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker; Kubernetes is a plus).
Excellent communication skills and the ability to work cross-functionally with technical and non-technical stakeholders.
Self-starter mindset with a passion for clean, documented, and tested data code
High impact and high velocity environment with the most talented and ambitious people you will ever work with
A chance to shape the story of a company and a category from the ground up
Real ownership. You’ll have the freedom and trust to build, test, and take lead
A product used by the best brands around the world
Hybrid working with an office in the heart of New Cairo
Regular team events, activities and off-sites
Competitive salary and equity package
27 days of annual paid vacation
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Cairo, Egypt
- A product used by the best brands around the world - Hybrid working with an office in the heart of New Cairo - Regular team events, activities and off-sites
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