

Customer Operations Department – Digikala
Digikala’s Customer Operations Department is looking for a Data Analyst to turn operational and system data from the contact center into actionable insights.
This role requires a strong ability to extract and process data from multiple databases and sources, as well as the analytical depth to measure the impact of operational changes and excellence initiatives, and present clear, data-driven recommendations to support decision-making.
Extract data from databases and multiple sources using SQL and system/file integrations.
Design, build, and maintain analytical datasets and data models required by the contact center.
Develop and maintain standardized operational and management dashboards using BI tools.
Perform deep-dive and ad-hoc analyses for operational challenges and excellence initiatives, including:
Root cause analysis
Opportunity identification
Impact measurement
Define and standardize contact center KPIs and improvement metrics.
Implement lightweight ETL / ELT data pipelines to reduce manual data handling.
Collaborate closely with product, process, and automation teams to interpret data and translate insights into action.
Ensure data quality, and continuously monitor anomalies, deviations, and critical alerts.
Education: Bachelor’s or Master’s degree in Industrial Engineering from top-tier public universities.
Experience:
4–6 years of hands-on experience in data analytics or BI roles within operational environments (e-commerce, logistics, marketplace, or service organizations).
Strong, production-level SQL skills, including:
Complex joins, window functions, CTEs, and query optimization
Experience working with large-scale databases (PostgreSQL, MySQL, SQL Server, BigQuery, or similar)
Advanced proficiency in at least one of the following:
Python for analysis and automation (pandas, numpy, Jupyter)
Or equivalent experience using R
Experience building dashboards using BI tools such as Power BI, Tableau, Looker, Metabase, or similar.
Strong impact analysis and problem-solving skills, including:
Before/after analysis
Cohort and segmentation analysis
Trend and anomaly detection
Experience with A/B testing or quasi-experimental methods is a strong plus
Ability to deliver clear data storytelling for operational leaders, including insights, conclusions, and recommended actions.
A strong portfolio of defensible, real-world projects.
Mandatory: Ability to present at least two production-grade analyses or dashboards with clearly defined KPIs and measurable impact.
Operational, action-oriented mindset
Speed and efficiency in data extraction and analysis
High attention to detail and strong data quality sensitivity
Ability to work in ambiguous, multi-stakeholder environments
Clear communication with non-technical and non-data stakeholders
Experience designing Data Marts or semantic layers for BI.
Familiarity with Airflow, dbt, or lightweight data pipeline tools.
Experience working with log, event, or behavioral data.
Knowledge of data quality frameworks and monitoring practices.
Prior experience in large or high-growth startups is a strong advantage.
If you believe you meet these qualifications and are interested in working in a dynamic, fast-paced environment, please submit your resume for consideration.
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