Data Engineer and Senior Data Analyst

CHANDRIKA GADIPARTHI

Data Engineer & Senior Data Analyst Data Pipelines, Warehousing & Analytics

214-***-**** *********************@*****.*** linkedin.com/in/chandrika-gadiparthi

PROFESSIONAL SUMMARY

Data Engineer and Senior Data Analyst with 7+ years of experience building reliable data pipelines and turning high-volume transactional data into trusted, decision-ready insights. Strong in SQL/PL-SQL, Python, ETL/ELT development, data warehousing (DWH/ODS/OLTP), and cloud data platforms, with current hands-on experience building and optimizing data pipelines on Azure Databricks and Azure Data Factory, plus AWS and GCP, along with data validation, lineage, and governance. Pairs engineering discipline (pipeline monitoring, DEV/UAT/PROD release validation, workflow automation) with analytics delivery in Power BI and Tableau for executive stakeholders. Proven track record at Verizon and EY in anomaly detection, root-cause analysis, and cross-functional work with DBA, DevOps, and engineering teams, applying AI/ML and LLM-assisted tooling to speed up data quality checks and incident resolution.

TECHNICAL SKILLS

Data Engineering

ETL/ELT Pipeline Design & Development, Azure Databricks, Apache Spark (PySpark), Airflow, dbt (data build tool), Kafka, EMR / EMR Serverless, AWS Step Functions, Batch & Streaming Processing, Data Lineage

Cloud Platforms

AWS (S3, Lambda, Glue, Redshift, EMR, EMR Serverless, Step Functions), Azure (Databricks, Data Factory, Synapse, Delta Lake, ADLS Gen2), GCP (BigQuery, Dataflow)

Databases & Warehousing

SQL (Advanced), PL/SQL, Oracle, MySQL, PostgreSQL, MongoDB, Elasticsearch, Snowflake, BigQuery, Redshift, Azure Synapse; Data Warehousing & Data Modeling (DWH/ODS/OLTP)

Programming & Automation

Python (Pandas, NumPy), SQL/PL-SQL, OPAL (Observe Processing and Analysis Language), Regex, REST API Integration & Testing (Postman), Workflow Automation

BI & Analytics

Power BI (DAX, Power Query), Tableau, Looker, Databricks SQL Analytics, Excel (Advanced), KPI & Regulatory Reporting, Predictive Analytics, Anomaly Detection, Root-Cause Analysis

Data Quality & Governance

Data Validation & Reconciliation, Data Quality Frameworks & MDM, Data Lineage, Data Dictionaries, Observability & Log Analytics

AI & ML Tools

Scikit-learn, OpenAI API, LangChain, Azure AI Studio, Vertex AI, Hugging Face, Copilot for Data, NLP

DevOps & Tools

Git, GitOps, CI/CD Pipelines, Terraform (IaC), Jenkins, Docker (basic), JIRA, Google Analytics

PROFESSIONAL EXPERIENCE

Senior Data Analyst Verizon Telecommunications January 2024 – Present

•Collaborated with ETL, DBA, and Data Engineering teams to trace data lineage across APIs, microservices, and backend databases, supporting reliable end-to-end data flow.

•Built and optimized ETL/ELT pipelines on Azure Databricks (PySpark, Delta Lake) orchestrated with Azure Data Factory to ingest and transform large-scale telecom datasets from ADLS Gen2 for downstream analytics.

•Migrated legacy batch jobs to Azure Databricks notebooks and Delta Lake tables, improving pipeline performance and enabling scalable, cost-efficient Spark-based data processing.

•Authored and optimized complex SQL/PL/SQL queries across large-scale OLTP datasets, supporting analytics and reporting on 10M+ customer records.

•Performed data validation between REST API outputs and Oracle backend systems, ensuring end-to-end consistency and SLA compliance.

•Modeled and monitored data pipelines using OPAL (Observe Processing and Analysis Language), applying observability and log analytics to detect pipeline and production issues early.

•Integrated AI-assisted log analysis tools to surface patterns in unstructured log data, reducing time-to-resolution on production incidents.

•Deployed AI-assisted anomaly detection using Python and Scikit-learn to identify PERK failure patterns, reducing manual investigation time by 40%.

•Leveraged LLM-powered tools (OpenAI API, Copilot) to accelerate root-cause analysis on API failures and subscription data discrepancies.

•Built Power BI dashboards with DAX measures to monitor KPIs, data quality scores, and system performance metrics for executive stakeholders.

•Supported data governance initiatives by maintaining data dictionaries, lineage documentation, and quality control frameworks.

Data Analyst / Consultant EY Banking Client January 2021 – October 2023

•Monitored and validated ETL transformation logic across DEV, UAT, and PROD environments during critical release cycles.

•Investigated and resolved data anomalies across Data Warehouse, ODS, and OLTP systems, improving data accuracy across 5+ interconnected platforms.

•Automated recurring data validation workflows using Python scripts, reducing manual effort by ~30% and minimizing human error in production reports.

•Designed and maintained complex SQL queries and stored procedures against Oracle databases to support KPI tracking and regulatory reporting.

•Applied Python (Pandas, NumPy) and AI-assisted data profiling tools to analyze large financial datasets and surface data quality issues proactively.

•Applied NLP and text analytics techniques (Regex, tokenization) to clean and transform unstructured financial data for downstream reporting.

•Built multi-stage OPAL pipelines chaining verbs such as filter, make_col, and statsby, where each stage fed the next, improving query efficiency and dataset reusability.

•Designed OPAL subqueries to independently shape and pre-process multiple dataset inputs before combining them, reducing redundant intermediate datasets in complex data-shaping tasks.

•Authored filter expressions using OPAL Boolean logic and the inexact-match operator to isolate events matching specific conditions across large-scale log datasets.

•Leveraged Tableau and Power BI for interactive dashboards; integrated predictive trend analysis to provide forward-looking business insights.

•Partnered with data governance and compliance teams to ensure data definitions, lineage, and reporting standards aligned with regulatory requirements.

Data Analyst Verizon India Operations January 2019 – December 2020

•Supported production break/fix activities, including validation of data loads and ETL transformation outputs across enterprise applications.

•Wrote and optimized complex SQL/PL/SQL queries for data validation, debugging, and backend analysis on high-volume OLTP systems.

•Analyzed application logs and database records using SQL and Python to identify system failures, data inconsistencies, and performance bottlenecks.

•Collaborated with DevOps and backend engineering teams to improve data reliability and system performance through data-driven RCA.

•Created automated reporting templates in Excel and early BI tools to support team metrics tracking and operational decision-making.

CERTIFICATIONS & TRAINING

•Microsoft Certified: Azure Data Fundamentals (DP-900) — In Progress / Target Q3 2026

•Google AI Essentials Certificate — Google (2025)

•NVIDIA Generative AI Explained — NVIDIA Deep Learning Institute (2025)

•Tableau Desktop Specialist — Tableau / Salesforce

•Advanced SQL for Data Science — Coursera / LinkedIn Learning

EDUCATION

Bachelor of Technology — Computer Science & Engineering

Koneru Lakshmaiah Education Foundation, Vijayawada, India Graduated: April 2019

ADDITIONAL COMPETENCIES

•Strong communicator with experience presenting data insights to both technical teams and C-suite stakeholders.

•Rapid learner with proven ability to adopt emerging AI and cloud data tools in fast-paced enterprise environments.

•Experienced in Agile/Scrum environments using JIRA for sprint tracking, backlog grooming, and cross-team coordination.

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