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Data Analyst with 5+ years in Data Modelling, ETL, and Cloud Data Warehousing
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Assessing your cultural and operational fit
Results-driven Senior Data Analyst with 5+ years of experience transforming complex datasets into actionable business insights. Proficient in SQL, Python, Power BI, Tableau, Databricks, Snowflake, BigQuery, and PostgreSQL. Proven track record in designing ETL pipelines, building scalable data models, developing interactive dashboards, and improving data processing efficiency using Apache Spark and cloud-native platforms. Experienced in e-commerce analytics, financial reporting, and cloud data warehousing, with a consistent focus on enabling data-driven decision-making across cross-functional teams.
Biju Patnaik University of Technology (BPUT)
Bachelor of Engineering
August 1, 2017 – June 30, 2021
Newaetate Pvt. Ltd
Senior Data Analyst
November 1, 2020 – Present
Bhubaneshwar, Odisha, India
Meesho E-Commerce Analytics Platform
January 1, 2021 – June 30, 2026
Led end-to-end Exploratory Data Analysis (EDA) on large-scale e-commerce datasets using Python (Pandas, NumPy, Matplotlib) and Apache Spark, identifying high-impact growth opportunities and revenue leakage patterns that informed strategic product decisions. Architected and deployed interactive Power BI dashboards with optimized DAX measures and data models, enabling real-time monitoring of critical KPIs—conversion rate, GMV, and customer retention—adopted by senior leadership for weekly business reviews. Designed and implemented dimensional data models in Snowflake and BigQuery to consolidate customer purchase data across multiple channels, enabling cohort-level behavioral analysis that reduced churn by surfacing at-risk customer segments for targeted retention campaigns. Built and optimized scalable ETL pipelines using Apache Spark and Databricks, ingesting and transforming data from 5+ sources into a centralized Snowflake reporting layer, reducing data latency by 60% and enabling near-real-time business reporting. Spearheaded A/B test analysis on product listing and pricing strategies using Python (SciPy, statsmodels), delivering statistically significant insights that contributed to a 12% uplift in average order value and directly influenced the product roadmap for Q3 2023. Developed a PostgreSQL-backed automated data quality framework to validate ingested datasets across 10+ pipelines, enforcing schema contracts, null-checks, and anomaly detection rules that reduced downstream reporting errors by over 80%. Collaborated with product and engineering teams to define a unified data catalog and KPI taxonomy covering 30+ business metrics, standardizing definitions across sales, marketing, and operations to ensure consistent reporting and eliminate cross-team data discrepancies.
Cultural Fit Analysis
The candidate's experience across diverse projects (e-commerce, financial analytics, website analytics) and their collaboration with various business units (product, engineering, sales, marketing, operations) suggest a strong adaptability and ability to integrate into different team cultures. Their focus on standardizing KPIs and data taxonomies indicates a commitment to fostering a data-driven culture. The continuous improvement mindset, as evidenced by efficiency gains and automation, aligns well with dynamic, growth-oriented environments.
Soft Skills & Operational Fit
The candidate demonstrates strong operational fit through their experience in automating reporting workflows, improving data processing efficiency, and collaborating with cross-functional teams. Their project descriptions highlight a proactive approach to problem-solving and a focus on delivering tangible business value. The emphasis on data quality, governance, and stakeholder communication indicates a mature approach to data analytics operations.