Senior Analytics Engineer - Marketing Data

Jobgether SRL; Portugal; Remote; EUR 70,000 - 95,000; Full time

Benefits offered by this job

Remote work

Long-term engagement

Technical impact

Job summary

Jobgether SRL in Portugal seeks a Senior Analytics Engineer - Marketing Data to design and optimize data models that empower marketing insights. You will work with Snowflake, SQL, Python, and Google Analytics to build scalable data solutions.

Collaborate with stakeholders, ensure data quality, and apply CI/CD practices in a remote-friendly environment. This role demands 5+ years in analytics/data engineering and a strong business sense.

Qualifications

• 5+ years in analytics engineering, data engineering, marketing data, or a closely related field.
• Hands-on Google Analytics data in production environments.
• Experience supporting data initiatives within retail or e-commerce.
• Advanced SQL skills for Snowflake data models and transformations.
• Python proficiency to read, debug, and optimize code.

Responsibilities

• Design, develop, and maintain scalable Snowflake data models.
• Work with Google Analytics data in production.
• Optimize SQL queries and Python code for reliability.
• Translate API docs into practical data integrations.
• Implement data validation across pipelines.
• Apply Git-based workflows with CI/CD.
• Collaborate with stakeholders to turn requirements into specs.
• Identify improvements in data models and pipelines.

Skills

SQL

Python

Data modeling

Data quality

CI/CD

Stakeholder management

English communication

Tools

Snowflake

Google Analytics

APIs

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer - Marketing Data based in Portugal.

Join a data-driven environment where analytics engineering plays a key role in transforming marketing data into actionable business insights.
In this role, you will design and optimize data models that support marketing analytics and business decision-making.
You will work extensively with Google Analytics data, Snowflake, SQL, and Python to build reliable, scalable data solutions.
Partnering with business stakeholders, you will translate complex requirements into clear technical deliverables.
You will help ensure data quality, consistency, and accuracy throughout the entire data pipeline.
Working within a collaborative, version-controlled development environment, you will contribute to robust engineering practices and continuous improvement.
This opportunity is ideal for an experienced analytics engineer who combines strong technical expertise with business understanding and a proactive, problem-solving mindset.

Accountabilities

• Design, develop, and maintain scalable data models, transformations, and materializations in Snowflake to support marketing analytics and business reporting.


• Work hands-on with Google Analytics data in a production environment, ensuring that marketing data is accurately structured and readily available for analysis.


• Develop, review, troubleshoot, and optimize SQL queries and Python code to improve data processing, reliability, and performance.


• Analyze API documentation and translate endpoints, objects, fields, and identifiers into practical data integration solutions aligned with business requirements.


• Implement and maintain data validation practices across multiple stages of data pipelines to ensure data integrity, consistency, and accuracy.


• Apply Git-based development workflows, including version control, code reviews, testing, and CI/CD practices, to maintain high engineering standards.


• Collaborate with stakeholders to gather requirements, clarify ambiguous business needs, structure discussions, and translate findings into precise, actionable technical specifications.


• Identify opportunities to improve data models, transformation logic, pipeline reliability, and overall analytics engineering processes.

Requirements

• At least 5 years of relevant professional experience in analytics engineering, data engineering, marketing data, or a closely related field.


• Hands-on professional experience working with Google Analytics data in a business or production environment. Academic coursework, certifications, or self-directed projects alone do not meet this requirement.


• Professional experience supporting data initiatives within a retail or e-commerce environment.


• Advanced SQL skills, including experience designing fit-for-purpose data models, transformations, and materializations in Snowflake.


• Working proficiency in Python, with the ability to read, evaluate, debug, troubleshoot, and improve code written by others.


• Experience interpreting API documentation and mapping API endpoints, objects, fields, and identifiers to business and technical requirements.


• Practical experience with Git and version-controlled development workflows, including code reviews, testing, and CI/CD.


• Strong understanding of data quality and validation techniques across different stages of a data pipeline.


• Excellent stakeholder management and requirements-gathering skills, with the ability to bring structure to ambiguous discussions and turn business needs into clear technical solutions.


• Exceptional written and verbal communication skills in English, with the ability to communicate technical concepts clearly to both technical and non-technical audiences.


• A proactive, analytical, and detail-oriented mindset, combined with strong problem-solving skills and the ability to work effectively in a remote environment.

Benefits

• Remote work: Work remotely from Anywhere, offering flexibility in your working environment.


• Long-term engagement: An opportunity to contribute to ongoing data engineering and marketing analytics initiatives through a long-term contract.


• Technical impact: Work with modern data technologies, including Snowflake, SQL, Python, Google Analytics, and API integrations.


• Business exposure: Collaborate with stakeholders to solve meaningful business challenges and support data-informed decision-making.


• Professional development: Strengthen your expertise in analytics engineering, data modeling, marketing data, and scalable data pipeline development.