Data Analyst Power Bi

Akanksha Gurram

Data Engineer / Data Analyst

Phone: +1-314-***-**** Email: ******************@*****.***

SUMMARY

Analytical and results-driven Data Analyst with 3+ years of experience turning complex data into actionable insights to support high-impact business decisions. Proven track record of designing and automating end-to-end reporting solutions using SQL, Excel, and BI tools like Power BI and Tableau. Adept at managing data integrity, optimizing ETL workflows, and identifying root causes through deep-dive analyses. Skilled in synthesizing large datasets to uncover trends and performance drivers and translating findings into executive-level dashboards.

Possesses strong business acumen and the ability to work across cross-functional teams in fast-paced, ambiguous environments. Demonstrated ability to independently own and deliver data projects from concept to deployment. Passionate about improving operational efficiency through data storytelling, process improvement, and innovation.

TECHNICAL SKILLS

●Languages & Tools: SQL, Python (Pandas, NumPy, matplotlib), Excel (pivot tables, VLOOKUP, macros), VBA, Git

●BI Tools: Tableau, Power BI

●Databases: SQL Server, PostgreSQL, Redshift, Oracle

●Cloud & ETL: AWS (S3, Redshift, EC2), Azure Data Factory, SSIS

●Web Basics: HTML5, CSS, JavaScript (React, basic exposure)

PROFESSIONAL EXPERIENCE

Data Analyst

Client: EDWARD JONES

JAN 2023 – March 2025 Saint Louis, MO

Designed and automated business intelligence dashboards in Tableau and Power BI, tracking KPIs across operations, resulting in a 35% improvement in reporting efficiency.

Developed custom SQL queries to extract, filter, and aggregate large datasets from AWS Redshift and Azure Synapse for in-depth analysis.

Wrote VBA scripts and Excel macros to streamline manual reporting processes, reducing recurring task time by 60%.

Built data pipelines using Azure Data Factory to ingest and transform data from Salesforce, on-prem SQL Server, and Excel files.

Maintained 99.9% data accuracy by implementing data validation, consistency checks, and anomaly detection scripts in Python.

Partnered with business stakeholders to define and refine analytical requirements for weekly and monthly reporting packages.

Led deep-dive investigations into customer service defects and operational inefficiencies using root cause analysis techniques.

Created a standardized framework for reporting campaign performance metrics, improving marketing ROI tracking by 25%.

Integrated Power BI dashboards with Excel data models for flexible reporting, allowing real-time filtering and drill downs by business unit.

Optimized Tableau data extracts and dashboard performance for large datasets, reducing load times by over 50%.

Conducted trend and cohort analysis for product performance across quarters, helping drive product lifecycle decisions.

Automated daily KPI reports using Python scripts and SQL jobs integrated with cloud storage and notification triggers.

Created and maintained technical documentation for ETL processes, KPIs, and reporting logic for stakeholder transparency.

Coordinated with engineering teams to validate upstream data pipelines and ensure end-to-end data integrity.

Presented findings and insights to non-technical stakeholders using data storytelling techniques and intuitive visualizations.

Key Tools: SQL, Tableau, Power BI, Excel (Pivot Tables, VBA, VLOOKUP), Python, AWS Redshift, Azure Data Factory, Salesforce

Junior Data Analyst

ACCENTURE – HYDERABAD

June 2020 – DEC 2021

Assisted in extracting, cleaning, and transforming raw datasets using SQL and Python for use in regular reports and dashboards.

Supported business stakeholders by generating ad hoc reports in Excel and Tableau based on operational and financial metrics.

Developed standardized Excel reports using pivot tables, charts, and formulas to track weekly sales and product performance.

Created basic visual dashboards in Tableau to monitor KPIs like order fulfillment rate, customer churn, and defect trends.

Worked with cross-functional teams to identify key metrics and improve data quality for critical business processes.

Wrote SQL queries to retrieve and analyze transactional data from relational databases (SQL Server and Oracle).

Validated and reconciled data between legacy systems and new platforms during migration initiatives.

Identified inconsistencies and anomalies in data using conditional logic in Excel and flagged them for correction.

Participated in internal QA and data verification procedures to ensure accuracy of published reports.

Collaborated with senior analysts to interpret results of statistical analyses and present insights to non-technical teams.

Documented procedures and created user guides to support reproducibility and onboarding of new team members.

Helped automate repetitive reporting tasks using Excel macros and scheduled queries in SQL.

Conducted daily audits of over 60 driver incident support tickets, identifying and flagging PII and safety issues using Excel pivot tables to streamline processing and ensure 100% SLA compliance.

Analyzed GPS and timestamp data in Tableau to reconstruct incident timelines, improving resolution accuracy by 15% and enabling data-driven decision making for 23-member operations team

Maintained organized documentation of queries, reports, and dashboard specs for reuse and auditing purposes.

Collaborated with Legal, Compliance, and Customer Support teams via SharePoint to coordinate case escalations and drive a 20% reduction in incident cycle time through automated workflow tracking.

Assisted in conducting market and competitor research using external datasets and internal KPIs to support strategy meetings.

Provided data support for customer experience surveys and product feedback analysis.

Key Tools: SQL, Excel, Tableau, Python (pandas), PowerPoint

EDUCATION

BACHELORS IN COMPUTER SCIENCE: 2020

Master’s in computer science: 2023

CERTIFICATIONS

●AWS Certified Solutions Architect – Associate

●Microsoft Certified: Azure Data Engineer Associate

●Tableau Desktop Specialist.

PROJECTS

1. Data Quality Monitoring Dashboard

●Created an automated dashboard in Power BI to monitor product return rates and identify anomalies.

2. ETL Pipeline for Customer Insights

●Developed a pipeline using SQL + Python to ingest and clean customer data, improving segmentation accuracy by 25%.

TECHNICAL PROFICIENCY

●Data Engineering: Hadoop, Spark, MapReduce, PySpark

●Cloud: AWS (EC2, S3, Redshift, Lambda, Glue), Azure (Data Factory, Data Bricks)

●BI & Reporting: Power BI, Tableau,

●Programming: Python, SQL, PL/SQL, T-SQL

●Version Control: GitHub,

●Databases: MS SQL Server, PostgreSQL,

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