Data Analytics Professional with Pipeline Automation

AMULYA PITTALA

***************@*****.*** +1-205-***-**** Birmingham, AL

PROFESSIONAL SUMMARY

Insight-driven Data Analyst with 4 years of progressive experience in transforming complex datasets into actionable insights and strategic recommendations across technology, finance, and marketing domains. Proficient in SQL, Python, Power BI, and Azure Data Factory, with expertise in building automated ETL pipelines, developing scalable dashboards, and performing statistical and predictive analyses to support data-driven decision-making. Adept at collaborating with cross-functional teams to enhance data quality, streamline reporting, and deliver measurable business impact using Snowflake, SQL Server, and cloud data engineering tools. CORE SKILLS

Programming & Analytics: Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, R Data Visualization: Power BI, Tableau, Excel (Pivot, Macros), Looker Databases & ETL: SQL Server, Snowflake, MySQL, PostgreSQL, SSIS, Azure Data Factory Cloud & Big Data: Azure Synapse, Azure Data Lake, AWS S3, Redshift, PySpark Statistical Methods: Regression, A/B Testing, Hypothesis Testing, Time Series Forecasting Other Tools: GitHub, Jira, Confluence, Agile Scrum PROFESSIONAL EXPERIENCE

Merkle Inc. Data Analyst Jun 2025 – Present Dallas, TX

Designed and implemented Power BI dashboards tracking multi-channel campaign performance, customer segmentation, and ROI metrics for executive stakeholders.

Built automated Azure Data Factory pipelines to ingest and clean marketing and sales data from 5 sources, cutting manual reporting time by 40 %.

Wrote optimized SQL stored procedures and window functions for aggregating billions of records with sub-second query latency.

Partnered with cross-functional teams to define KPIs and data governance rules, ensuring a single source of truth across departments.

Utilized Python (Pandas + Matplotlib) to build trend and forecast models that improved budget planning accuracy by 15 %.

Migrated legacy Excel reporting to Power BI Service workspaces with row-level security and refresh scheduling.

Conducted root-cause analysis on data discrepancies between Azure Synapse and Snowflake, enhancing data integrity checks by 30 %.

Presented quarterly insight decks to directors highlighting customer growth, cost trends, and campaign conversion drivers. 3i Infotech Reporting Analyst Jan 2021 – Jul 2023 Hyderabad, India

Developed interactive Power BI dashboards for operations and finance, tracking real-time KPIs on cost centers and service delivery.

Automated data integration between on-prem SQL Server and Azure Synapse using ETL packages and Python scripts.

Created parameterized SQL reports for C-suite stakeholders, reducing manual data processing time by 50 %.

Enhanced data accuracy through data profiling and validation frameworks, eliminating ~25 % of duplicate records.

Coordinated with data engineers to standardize naming conventions and metadata documentation for governance compliance.

Leveraged Excel VBA automation to compile weekly SLA and incident trend reports, accelerating turnaround by 60 %.

Supported financial forecasting efforts with Python statistical libraries, identifying variance drivers and outliers.

Presented bi-weekly data insight summaries to management to drive resource optimization initiatives. Sasken Technologies Data Intern Jan 2020 – Dec 2020 Hyderabad, India

Assisted senior analysts in data collection and cleansing for product performance and QA analytics projects.

Built Tableau dashboards and Excel pivot reports to visualize testing defect trends and resource utilization.

Used Python and SQL to aggregate log data and highlight inefficiencies in software testing cycles.

Conducted ad-hoc analyses to identify release bottlenecks, contributing to a 12 % faster deployment timeline.

Documented query scripts and dashboard procedures in Confluence to improve team knowledge transfer.

Collaborated with QA and engineering teams to standardize data capture templates for post-release reporting. EDUCATION

University of Alabama at Birmingham — Master of Science in Computer Science (GPA 3.41) May 2025 St. Martin’s Engineering College — Bachelor of Technology in Information Technology Aug 2017 – Jun 2021 CERTIFICATIONS

Fundamentals of Machine Learning with Python

Implementation (AZ-104)

HTML5 – Basics to Advanced

Microsoft Azure Fundamentals (AZ-900)

PROJECT HIGHLIGHTS

Customer Segmentation Model: Applied unsupervised machine learning (k-means) on transaction data to segment customers, improving targeting accuracy by 20 %.

ETL Automation Pipeline: Orchestrated data ingestion from five business systems using Azure Data Factory and SQL, reducing manual reporting time by 45 %.

Sales Forecast Dashboard: Developed Power BI forecast visuals using DAX measures to predict quarterly revenue with a 8 % variance.

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