Data Analyst
Data Analyst at WorkFlowX Technologies (Remote). 3 Yrs experience, 0.3-0.4 Lacs PA. Overview We are seeking a detail-oriented Data Analyst to join a…
- Company
- WorkFlowX Technologies
- Location
- Remote
- Work mode
- Remote
- Job type
- Full-time
- Experience
- 3 Yrs
- Salary
- 0.3-0.4 Lacs PA
- Posted
- 2026-10-07
- Industry
- Technology
Job description
Overview
We are seeking a detail-oriented Data Analyst to join a fast-paced, collaborative team that turns data into actionable insights. In this role you will partner with product, marketing, and operations to design analyses, build dashboards, and translate complex data into clear recommendations that drive business decisions and measurable outcomes.
The Data Analyst will own recurring reports, ad-hoc analyses, and data quality initiatives while helping improve data instrumentation, pipeline reliability, and self-serve analytics. You will have the opportunity to shape KPIs, influence product roadmaps, and mentor others on best practices for data-driven decision making.
Responsibilities
• Design, execute, and maintain robust analyses that answer business questions and inform strategic decisions.
• Build, maintain, and improve dashboards and visualizations using BI tools (e.g., Tableau, Looker, Power BI).
• Write efficient SQL queries to extract, transform, and aggregate data from relational and cloud data warehouses.
• Perform data cleaning, validation, and transformation to ensure accuracy and reproducibility of analytic outputs.
• Develop and monitor key performance indicators (KPIs), create automated reporting, and identify trends, anomalies, and opportunities.
• Collaborate with cross-functional partners to define metrics, measurement frameworks, and A/B testing methodologies.
• Document analyses, data definitions, and reporting processes to ensure transparency and enable self-serve analytics.
• Partner with data engineering to improve data pipelines, instrumentation quality, and schema design.
• Present findings and recommendations clearly to technical and non-technical audiences; influence decision-making with storytelling and evidence.
• Participate in ad-hoc projects, including forecasting, segmentation, and model evaluation, as business needs evolve.
Qualifications
• Bachelor's degree in a quantitative field or equivalent practical experience.
• 2+ years of professional experience in a data analyst or similar role.
• Strong SQL skills with experience writing complex, performance-aware queries.
• Proficiency with Python or R and libraries for data manipulation and visualization.
• Experience building dashboards and visualizations in tools such as Tableau, Looker, or Power BI.
• Solid understanding of statistics, experimental design, and A/B testing.
• Familiarity with cloud data warehouses (BigQuery, Snowflake, Redshift) and ETL/ELT concepts.
• Excellent communication skills and ability to translate complex analyses into actionable recommendations.
• Strong problem-solving mindset, attention to detail, and commitment to reproducible work.
• Experience with data modeling, governance, and version control (Git) is a plus.
Responsibilities
- Design, execute, and maintain robust analyses that answer business questions and inform strategic decisions.
- Build, maintain, and improve dashboards and visualizations using BI tools (e.g., Tableau, Looker, Power BI) for product, marketing, finance, and operations teams.
- Write efficient SQL queries to extract, transform, and aggregate data from relational and cloud data warehouses (e.g., Postgres, Redshift, BigQuery, Snowflake).
- Perform data cleaning, validation, and transformation to ensure accuracy and reproducibility of analytic outputs.
- Develop and monitor key performance indicators (KPIs), create automated reporting, and identify trends, anomalies, and opportunities.
- Collaborate with cross-functional partners to define metrics, measurement frameworks, and A/B testing methodologies.
- Document analyses, data definitions, and reporting processes to ensure transparency and enable self-serve analytics.
- Partner with data engineering to improve data pipelines, instrumentation quality, and schema design.
- Present findings and recommendations clearly to technical and non-technical audiences; influence decision-making with storytelling and evidence.
- Participate in ad-hoc projects, including forecasting, segmentation, and model evaluation, as business needs evolve.
Key skills
SQL, Python or R, Statistics & A/B Testing, Data Modeling & ETL, Excel/Spreadsheets, Communication & Data Storytelling, Problem Solving & Critical Thinking, Version Control (Git), mysql
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