Data Analyst- Product Owner
Why This Role Stands Out
This Data Analyst-Product Owner role offers a fantastic opportunity to shape product strategy and drive impactful data-driven decisions within a reputable company. You'll thrive here if you're adept at bridging technical and business needs, eager to develop leadership skills, and excited by a collaborative environment. Apply now to contribute to innovative solutions and advance your career.
Quick Overview
Job Description
Job Description:
|
Title |
Data Analyst- Product Owner |
|
location |
Dallas/Denver |
|
Type |
Contract |
|
Interview Mode: |
Either Phone or In Person. |
- Proven experience working in a large-scale enterprise environment, preferably within the
- telecommunications industry.
- Solid understanding of data governance principles, data quality frameworks, metadata
- management, and data lineage.
- Familiarity with various data technologies and platforms (e.g., data warehouses, data lakes,
- ETL tools, cloud data services).
- Experience with Al-powered automation tools, particularly in data pipeline development,
- governance enforcement, and forecasting.
- Excellent communication, interpersonal, and presentation skills.
- Strong analytical and problem-solving abilities.
- Ability to work independently and as part of a team in a fast-paced environment.
- Certified Scrum Product Owner (CSPO) or equivalent certification is a plus.
- Knowledge of Data Warehouse and Data Lake.
Data Analyst
- Experience: 4-6 years
- Develop Data Solutions: Analysed, Design and build applications and data pipelines using
- AWS, Databricks, Redshift, and Snowflake.
- ETL/ELT Development: Analyze standards and procedures for, and design data extraction,
- transformation, and loading (ETL/ELT) processes for both batch and real-time data.
- Database Management: Design DataLakes and Data Warehouses, and work with databases like Oracle and SQL Server.
- SQL Expertise: Write advanced SQL queries, including performance tuning, to support data analysis and application needs.
- Full-Cycle Development: Handle the entire software development lifecycle for data warehouse applications, from requirements analysis to implementation, testing, and
- debugging.
- System Integration: Integrate, enhance, and fine-tune Enterprise Data Warehouses to consolidate data from various sources.
Skills
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