Data Analyst Business

SHIVANI M Data Analyst/ Business Analyst

Email ID: *********.****@*****.*** Ph: +1-816-***-****

PROFESSIONAL SUMMARY:

4+ years of experience in data engineering, data analysis, and business analysis, with a focus on designing scalable, reliable data solutions.

Proficient in building and optimizing ETL/ELT pipelines using tools like DBT, Talend, and Apache Airflow.

Extensive experience with SQL-based databases (PostgreSQL, Snowflake) and NoSQL databases (MongoDB, Apache Cassandra).

Skilled in spreadsheet tools (Excel, Google Sheets), including advanced formulas, pivot tables, data validation, and sheet protection.

Skilled in creating compelling data visualizations using Tableau, Power BI, and Looker to deliver actionable insights. Strong expertise in Python and SQL for automation, data transformation, and advanced analytics.

Hands-on experience with real-time processing technologies like Apache Kafka and Spark.

Expertise in cloud platforms including AWS (RDS, S3, Redshift), Azure (Data Factory, Data Lake), and GCP for data-driven projects.

Proven ability to communicate effectively, meet deadlines, and solve complex data challenges. Proven ability to collaborate with cross-functional teams and deliver solutions that meet business and technical requirements.

Strong analytical mindset and problem-solving skills, capable of handling ambiguous environments and translating abstract ideas into actionable insights.

Strong interpersonal and communication skills, with a proven ability to collaborate across departments to meet organizational goals. A continuous learner with curiosity-driven expertise in modern analytics tools and techniques.

TECHNICAL SKILLS:

Programming Languages

Java, Python, Shell Scripting

Big Data Technologies

Hadoop, HDFS, Sqoop, Hive, HBase, Apache Spark, PySpark, Kafka

MS Office Package

MS Word, MS Excel, MS PowerPoint, MS Teams

Database

MySQL, NoSQL (MongoDB), PostgreSQL, SQL Server, Oracle

Reporting Tools

Tableau, Power BI, SQL Server Reporting Services (SSRS)

Cloud Platforms

AWS, AZURE, GCP

Data Formats

XML, JSON, CSV, Parquet, Text, Log

Operating Systems

Windows, Mac

Web Technologies

HTML, CSS

Development Tools

Git, JIRA, Agile methodologies, API integration, GitLab

Machine Learning and AI

Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, scikit-learn, Deep Learning

ETL Tools

Informatica-Power Center, SSIS

Other Skills

Snowflake, Data Cleansing, Data Transformation, Data Migration, FTP Operations, Talend, CI/CD pipelines

PROFESSIONAL EXPERIENCE:

Client: Bank of Texas, Dallas, Texas July 2024 - Present

Position: Data Analyst

Streamlined real-time financial data workflows by integrating Kafka with Spark, reducing event detection latency by 20%.

Designed and optimized PostgreSQL-based data models, enhancing query performance by 25%.

Developed advanced SQL queries using window functions, enabling actionable insights for financial reporting.

Leveraged Azure Data Factory for robust ETL pipelines, reducing data processing time by 30%.

Implemented data governance practices, ensuring compliance through encryption and masking in Azure Data Lake.

Migrated large-scale on-premises data systems to Snowflake, reducing infrastructure costs by 30% and improving data accessibility.

Automated ETL workflows using Informatica, achieving a 25% reduction in load times and enhancing scalability.

Built interactive dashboards using Tableau and Power BI, delivering key insights for stakeholders.

Client: Celgene, Phoenix, Arizona December 2022 – May 2024

Position: Data Analyst/Business Analyst

Conducted sessions with the Business Analysts to gather the requirements. Provided assistance for health care projects through SAS statistical and analysis software tools.

Designed and automated ETL pipelines in AWS Glue, reducing manual intervention and improving efficiency by 40%.

Utilized AWS Redshift for centralized storage, enhancing query performance and analytics delivery.

Streamlined data ingestion workflows using AWS S3 and RDS, improving data availability by 30%.

Optimized batch and real-time data processing with PySpark, reducing processing time by 40%.

Designed and implemented scalable data warehousing solutions in Snowflake, optimizing storage and query performance by 40%

Conducted in-depth analysis using MongoDB, improving retrieval efficiency by 35%.

Created and deployed dynamic SSRS reports, enhancing cross-departmental accessibility.

Collaborated with business teams to transform requirements into impactful data stories, leveraging Tableau for visualization.

Organization: TA Digital, Hyderabad, India June 2020 - July 2022

Position: Software Developer

Designed and deployed scalable data pipelines using Hadoop HDFS and Apache Spark, reducing batch processing time by 30%.

Implemented real-time streaming pipelines with Kafka, ensuring timely data availability for analytics.

Enhanced PostgreSQL schema performance by 25% through optimization techniques and query tuning.

Automated CI/CD workflows using GitLab and AWS services, reducing deployment times by 50%.

Conducted data migrations with PL/SQL scripts, ensuring data integrity and accuracy.

Developed dashboards in Tableau, integrating real-time data from APIs for dynamic visualizations.

Leveraged Airflow DAGs for orchestrating reliable and automated workflows, reducing manual intervention by 40%.

Applied Agile methodologies to manage data analysis projects. Integrated real-time data from third-party APIs to enhance analysis.

Organization: Brain-o-vision Solutions, Hyderabad, India January 2020 - May 2020

Position: Machine Learning Engineer

Built and deployed machine learning models using scikit-learn and TensorFlow, achieving high accuracy through robust preprocessing.

Automated data cleaning processes with Python libraries (pandas, NumPy), improving data quality by 40%.

Developed interactive visualizations with Matplotlib and Seaborn, enabling stakeholders to derive actionable insights.

Designed scalable workflows to process and analyze large datasets efficiently, reducing execution times by 25%.

Conducted data analysis and feature engineering, improving machine learning model accuracy by 15%.

Collaborated with cross-functional teams to ensure timely project delivery and adherence to Agile workflows.

Documented processes and findings clearly, bridging gaps between technical teams and stakeholders.

CERTIFICATIONS:

Data Science and Big data from Dell EMC

AWS Cloud Practitioner

Data Analytics on Google Cloud

Programming for Everybody (Getting Started with Python) from Coursera

ACADEMIC PROJECTS:

Rice Crop Disease Detection through Deep Learning

Led development of rice disease detection system using YOLOv3 and Microsoft’s Visual Object Tagging Tool (VOTT).

Titanic Survival and Prediction using Machine Learning

Analyzed passenger data to assess survival probabilities during Titanic voyage using machine learning algorithms.

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