Data Analytics

hace 5 meses

Tlahuac, México Marriott Vacations Worldwide A tiempo completo

**Position Summary**:
As a member of the professional staff, contributes general knowledge and skill in a discipline area (e.g. Accounting, Finance, Human Resources, Information Resources, Operations Planning & Support, Sales & Marketing) to support team and/or department objectives. Generally, works under close supervision or within well-established guidelines to complete routine tasks.

**Specific Job Summary** (describe the nature and purpose of the position)

Results-driven and detail-oriented Data Analytics Engineer to help unlock the full potential of our data and drive the success of our data analytics strategy. The Data Analytics Engineer is expected to work closely and collaborate with cross-functional teams.

The Data Analytics Engineer gathers business requirements and translates these into data requirements to help IT build robust and streamlined data pipelines. The Data Analytics Engineer provides data requirements for data ingestion, transformation, and scheduling to empower insightful business reporting and advanced analytics readiness.

In addition, the Data Analytics Engineer validates and tests the accuracy, consistency, and readiness of the data and runs analyses to ensure the data meets the business needs. Moreover, the Data Analytics Engineer builds intuitive data models and semantic layers and develops user-friendly enterprise reports.

**Expected Contributions**:
**Option 1**
- Performs the following types of basic tasks: analysis, auditing, budgeting, forecasting, programming, research, report generation, and software integration.
- Responds to, solves, and makes decisions on standard/routine business requests with limited risk.
- Responsible for own work and contributing to team, department and/or business results. May direct work of non-management staff.
- Assists more senior associates in achieving business results by:

- utilizing technical knowledge and skills to enhance business processes.
- establishing priorities for self and, where appropriate, others.
- allocating own time effectively to meet goals in a manner that does not disadvantage other associates or groups.
- contributing to department/unit budget as appropriate (i.e., input, following guidelines, etc).
- Demonstrates an awareness of personal strengths and areas for improvement and acts independently to improve and increase skills and knowledge.
- Performs other duties as appropriate.

**Specific Expected Contributions** (including duties and responsibilities)
- Helps determine and assess data integration requirements for the enterprise data warehouse and communicates these requirements to IT
- Collaborates with business partners to translate reporting and advanced analytics requirements into data pipeline and modeling requirements
- Creates and optimizes data models and semantic layers that facilitate seamless and self-service data exploration and analysis
- Designs, develops, and maintains reports and dashboards using data visualization tools (e.g. Power BI, Cognos, Tableau, Looker) to help analyze complex datasets and enable actionable insights and recommendations
- Identifies redundant reporting and opportunities for consolidation
- Elaborates clear and straightforward technical documentation
- Guides and promotes self-service data accessibility within the organization

**Option 1**

Usually, a professional position with general knowledge in a discipline (i.e., Accounting, Human Resources, Information Resources). College degree and/or related experience typically required.
- Bachelor’s degree in Computer Science, Data and Information Systems, or a related field
- Minimum 2+ years of experience as a Data Analytics Engineer or similar role in a data-driven environment
- Work experience translating business requirements to data requirements
- Strong proficiency in programming languages such as SQL and Python
- Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud)
- Solid understanding of data modeling principles and best practices
- Experience with reporting and data visualization tools (e.g. Power BI, Cognos, Tableau, Looker) and UX fundamentals
- Preferred experience working with Agile methodologies
- Strong collaborative and communications skills
- Previous working experience with data pipeline orchestration tools and distributed data processing frameworks is a plus

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