Data Analyst Power Bi

DINESH CHANDRA MIDDE Data Analyst

IL, USA +1-224-***-**** ******************@*****.*** LinkedIn SUMMARY

Data Analyst with 3+ years of experience in transforming raw data into actionable insights using Python (pandas, NumPy), SQL (joins, CTEs, window functions), and R. Skilled in building robust ETL pipelines using Apache Airflow, AWS Glue, and Azure Data Factory, ensuring consistent and scalable data flow. Proficient in data visualization with Power BI, Tableau, and Google Data Studio, enabling teams to track KPIs and performance metrics. Applied A/B testing, hypothesis testing, and regression analysis to evaluate experiments and forecast trends. Experienced with Apache Spark, Hive, and cloud platforms like AWS, Azure, and GCP. Strong grasp of data governance, quality assurance, and compliance frameworks including HIPAA and GDPR.

SKILLS

Languages & Scripting: Python (pandas, NumPy), SQL (advanced queries, window functions), R (basic), Bash Data Manipulation & Analytics: EDA, Hypothesis Testing, Regression (Linear, Logistic), Time Series Forecasting, Chi-square Tests, A/B Testing, Experimentation Design, Data-Driven Decision Making Machine Learning & NLP: Scikit-learn, XGBoost, Random Forest, TensorFlow, Classification, Forecasting, spaCy, NLTK, TextBlob, VADER, BERT

Big Data & ETL Frameworks: Apache Spark (PySpark), Hive, Hadoop, Flink, Kafka (streaming), Talend, Informatica, Apache Airflow, Python-based pipelines, AWS Glue, Azure Data Factory Databases & Warehousing: MySQL, PostgreSQL, SQL Server, MongoDB, Cassandra, DynamoDB, Redshift, Data Lake Gen2 Visualization & BI Tools: Power BI, Tableau, Superset, Google Data Studio, Excel (Pivot Tables, Macros), Matplotlib, Seaborn, Plotly

Cloud & DevOps Platforms: AWS (S3, Lambda, RDS, Glue, Redshift, Athena), Azure (Data Factory, Synapse, Blob Storage), GCP

(BigQuery, Cloud Storage), Docker, Terraform

Monitoring, Logging & Testing: Prometheus, Grafana, ELK Stack, Azure Monitor, Log Analytics, Stackdriver, Datadog, New Relic, Jupyter Notebooks, pytest

Governance & Compliance: HIPAA, GDPR, CCPA, Data Lineage, Data Quality Control Project & Agile Methodologies: Agile, Scrum, Jira, Trello, Technical Documentation, TDD, Stakeholder Collaboration, Analyst Training

PROFESSIONAL EXPERIENCE

Data Analyst

Charles Schwab, IL, USA Jan 2024 – Present

Developed 20+ automated ETL pipelines using Airflow, AWS Glue, and SQL to streamline reporting for wealth management operations, reducing processing time by 35%.

Created interactive dashboards in Power BI and Tableau used by 8+ business units, improving executive reporting visibility and cutting ad hoc requests by 40%.

Conducted A/B testing and hypothesis-driven analysis on client portfolio performance, supporting changes that increased user engagement by 18%.

Applied regression and time series forecasting models using Python (scikit-learn, XGBoost) to predict trading volume, improving allocation accuracy by 22%.

Integrated Redshift, Athena, and S3 for secure, scalable storage and retrieval of trading data across 5+ departments.

Monitored ETL jobs and system performance using Grafana and ELK Stack, reducing incident resolution time by 27%.

Ensured compliance with GDPR and CCPA by enforcing data retention rules and conducting monthly audits on 50+ datasets. Data Analyst

Intex Technologies, India Mar 2021 – Jul 2022

Designed 15+ data pipelines using Python and SQL to integrate sales and marketing data, reducing manual effort by 50%.

Implemented data quality validation rules and anomaly detection scripts, catching 120+ inconsistencies monthly across three product lines.

Built predictive models with scikit-learn to forecast monthly sales by region, achieving 93% accuracy and guiding budget allocation.

Developed internal dashboards in Google Data Studio and Tableau to track SKU performance, reducing inventory waste by 14%.

Consolidated data from PostgreSQL, MongoDB, and Data Lake Gen2, enabling unified reporting across 10+ retail branches.

Collaborated with IT and QA to test pipeline performance, reducing latency by 30% and increasing data refresh frequency to daily.

Created documentation for 100% of data workflows and trained 4 junior analysts on using version control and Python- based tools.

Junior Data Analyst

Intex Technologies, India Jun 2020 – Feb 2021

Assisted in cleaning and structuring raw sales data using Python (pandas) and SQL, reducing data preparation time by 40%.

Created ad hoc visual reports using Excel and Power BI that helped senior analysts track regional sales KPIs weekly.

Supported development of rule-based data validation scripts, flagging 200+ records/month for manual review.

Documented all ETL testing outcomes, contributing to standardization of data validation processes across the analytics team.

Conducted exploratory analysis to identify top-performing products, influencing promotional campaigns in North and South India.

Participated in daily Agile standups and updated task progress in Jira, improving sprint planning efficiency.

Maintained confidentiality and access control for all datasets, adhering to internal audit requirements and data governance protocols.

EDUCATION

Master of Computer Engineering

Arizona State University, Tempe, AZ May 2024

Bachelors in Electronics and Communication Engineer SRM University, India May 2022 Relevant Coursework: Data Structures, Algorithms, Distributed Systems, Cloud Computing, Big Data Processing

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