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About Workpinnacle

Welcome to

Workpinnacle

, a global leader in retail technology and data-driven solutions. We empower millions of shoppers and partners by turning complex data into actionable insights that drive smarter decisions, faster. Our mission is simple: make retail smarter, faster, and more customer‑centric. With a culture rooted in innovation, collaboration, and continuous learning, Workpinnacle is the place where data professionals thrive and shape the future of commerce.

Why Workpinnacle?

At Workpinnacle, we believe that the right data can transform an entire industry. As a Remote Data Analyst, you’ll be at the heart of that transformation—turning raw numbers into stories that guide strategy, operations, and customer experience. Here’s what makes Workpinnacle a standout employer:

Remote Flexibility

– Work from anywhere while staying connected to a vibrant, global team.

Impactful Projects

– Your work directly influences millions of customers and partners worldwide.

Growth & Development

– Access to cutting‑edge training, mentorship, and career‑advancement pathways.

Inclusive Culture

– A diverse, supportive environment where every voice is heard.

Competitive Compensation

– $27 per hour, plus performance bonuses and equity opportunities.

Key Responsibilities

As a Remote Data Analyst – Data Entry Specialist, you will be responsible for ensuring the accuracy, integrity, and accessibility of Workpinnacle’s data assets. Your day‑to‑day tasks will include:

• Managing large, complex datasets across multiple sources and ensuring data quality through rigorous validation and cleansing.

• Designing, building, and maintaining ETL pipelines that extract, transform, and load data into our central data warehouse.

• Collaborating with cross‑functional teams—Product, Finance, Operations, and Customer Experience—to understand data needs and deliver actionable insights.

• Creating and maintaining interactive dashboards and reports using tools such as Tableau, Power BI, or Looker.

• Documenting data processes, data dictionaries, and best practices to support knowledge sharing and compliance.

• Identifying and troubleshooting data anomalies, and proposing solutions to improve data reliability.

• Participating in data governance initiatives, including data stewardship, metadata management, and security protocols.

• Mentoring junior analysts and sharing expertise on data tools, SQL, and Python scripting.

Essential Qualifications

We’re looking for candidates who bring a blend of technical skill, analytical mindset, and a passion for data. The following qualifications are essential:

• Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.

• Minimum of 2 years of experience in data analysis, data entry, or ETL development.

• Proficiency in SQL (MySQL, PostgreSQL, or similar) for data extraction, transformation, and reporting.

• Strong experience with Python (pandas, NumPy) or an equivalent scripting language for data manipulation.

• Hands‑on experience with data visualization tools (Tableau, Power BI, Looker).

• Excellent attention to detail and a commitment to data integrity.

• Effective communication skills—able to translate technical findings into clear, actionable insights for non‑technical stakeholders.

• Self‑motivated, organized, and capable of working independently in a remote setting.

Preferred Qualifications

While not mandatory, the following experience will set you apart:

• Experience in the retail or supply‑chain industry, especially with large‑scale transactional data.

• Familiarity with data governance frameworks and compliance standards (GDPR, CCPA).

• Knowledge of cloud data platforms (AWS Redshift, Snowflake, BigQuery).

• Experience with ETL tools such as Alteryx, KNIME, or Talend.

• Background in statistical analysis or machine learning concepts.

• Previous remote work experience with distributed teams.

Skills & Competencies

Success at Workpinnacle requires a blend of technical prowess and soft skills. Key competencies include:

Data Literacy

– Ability to interpret, clean, and transform data into meaningful insights.

Problem‑Solving

– Analytical thinking to diagnose data issues and propose effective solutions.

Collaboration

– Working seamlessly with cross‑functional teams to align data initiatives with business goals.

Adaptability

– Thriving in a fa