Senior Analytics Engineer - Marketing Data

Jobgether; United States; Remote; USD 97,000 - 125,000; Full time

Benefits offered by this job

Remote work

Long-term engagement

Modern data stack

Stakeholder collaboration

Professional development

Job summary

Jobgether is seeking a Senior Analytics Engineer – Marketing Data to design and optimize data models for marketing analytics, leveraging Snowflake, SQL, Python, and GA4 data in a remote, long-term engagement. You will work with stakeholders to translate requirements into robust data solutions and uphold data quality across the pipeline.

The role emphasizes strong engineering practices, CI/CD, and proactive problem solving in a remote environment, with 5+ years of relevant experience expected.

Qualifications

• 5+ years of analytics engineering or data engineering experience in marketing data.
• Hands-on experience with Google Analytics data in production.
• Experience with retail/e-commerce data is a plus.
• Strong SQL and Snowflake data modeling experience.
• Proficient Python and ability to read/improve code.
• Experience with Git and CI/CD workflows.
• Excellent communication and stakeholder mgmt in English.

Responsibilities

• Design and maintain scalable Snowflake data models and transformations for marketing analytics.
• Work with GA4 data in production to ensure accurate analysis.
• Develop and optimize SQL queries and Python pipelines to improve performance.
• Translate API documentation into practical data integration solutions.
• Ensure data quality and pipeline reliability across stages.
• Apply Git-based development workflows including reviews and CI/CD.
• Collaborate with stakeholders to turn business needs into technical specs.
• Identify opportunities to improve analytics engineering processes.

Skills

Marketing analytics

SQL

Python

Data modeling

Stakeholder mgmt

Tools

GA4

Snowflake

API integration

Git & CI/CD

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 Australia.

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.