MarTech Engineer (Adobe)
WillowTreeSalary not specified
Full Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Not SpecifiedCompensation
Junior (1 to 2 years), Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
TechnologyIndustries
Requirements
- Bachelor’s degree in computer science, Information Technology, or a related field
- 2-4 years of experience in QA, with a focus on tagging for digital analytics within Adobe ecosystem
- Proven experience in Quality Assurance, with a focus on Adobe Analytics tagging and tracking implementations (dot com and mobile app)
- Able to pull Adobe Analytics Workspace reports to validate feature tags
- Familiarity with Adobe Target
- Familiarity with HTML, JavaScript, and other web technologies
- Strong analytical and problem-solving skills
- Excellent communication and collaboration skills
- Detail-oriented and able to manage multiple tasks in a fast-paced environment
- Experience with testing automation tools is a plus
- Hands-on experience with PyTest, BDD framework, Appium, Python (preferred)
- Experience working with Android emulators and iOS simulators (preferred)
- Experience working with any cloud platform like SauceLabs, BrowserStack, or any equivalent tools (preferred)
- Experience working with CI/CD tools like GitLabs, or any equivalent tools (preferred)
- Experience working in Agile environments (preferred)
- Expertise in cloud platforms like Jenkins, Azure, and GitLab, and experience integrating CI/CD pipelines (preferred)
Responsibilities
- Conduct comprehensive quality assurance testing on digital tracking implementations, ensuring tags are firing correctly, and data is accurately captured
- Create and maintain detailed documentation of tagging requirements, standards, and testing procedures
- Work closely with development teams, product managers, and digital analysts to understand tagging requirements and business objectives
- Identify and troubleshoot tagging issues promptly. Collaborate with development teams to resolve any discrepancies or bugs in tracking implementations
- Explore and implement automated testing tools and scripts to streamline tagging QA processes
- Monitor and analyze tag performance and data accuracy over time. Provide insights and recommendations for improvements
- Stay abreast of industry trends, best practices, and emerging technologies related to digital tagging and analytics
Skills
Adobe Analytics
Adobe Launch
Adobe Target
Adobe Experience Platform
Tagging QA
QA Testing
Automated Testing
Digital Tracking
Performance Monitoring
ShyftLabs
Data-driven decision-making solutions for organizations
About ShyftLabs
ShyftLabs helps organizations adopt a data-first approach to their decision-making processes. Their services focus on establishing systems that enable companies to make quicker and more informed decisions based on data analysis. This approach allows businesses to gain insights that can keep them ahead of their competitors. Unlike other companies that may offer generic consulting services, ShyftLabs emphasizes the importance of data in driving decisions, ensuring that organizations can leverage their data effectively to enhance their strategic planning and operational efficiency.
None, CanadaHeadquarters
2018Year Founded
VENTURE_UNKNOWNCompany Stage
Data & Analytics, ConsultingIndustries
11-50Employees
Benefits
Health Insurance
Hybrid Work Options
Professional Development Budget
Risks
Increased competition from startups offering innovative, cost-effective solutions.
Growing demand for in-house analytics teams reducing reliance on consultants.
Rapid AI advancements may outpace ShyftLabs' current technology offerings.
Differentiation
ShyftLabs specializes in data governance, warehousing, and predictive analysis services.
The firm empowers organizations with a data-first approach for decision-making.
ShyftLabs establishes processes for faster, insightful decisions to outpace competition.
Upsides
Increased demand for data governance due to stricter privacy regulations.
Growing interest in predictive analytics in retail for inventory optimization.
Rising adoption of cloud-based BI tools among SMEs for cost-effectiveness.
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