Data Engineer Quality

Laya Tigulla

Irving, TX *************@*****.*** +1-940-***-**** linkedin.com/in/linkdinly

PROFESSIONAL SUMMARY

Data Engineer experienced in building and maintaining scalable data pipelines, optimizing ETL workflows, and deploying cloud-native solutions across Azure, GCP, and AWS. Proficient in transforming raw data into structured, analysis-ready datasets using tools such as Apache Spark, Airflow, SQL, and Python. Expertise in designing data lake and warehouse architectures, orchestrating data workflows, automating deployments, and ensuring data quality, security, and governance across enterprise-level systems.

CORE COMPETENCIES

ETL/ELT Pipelines: Airflow, dbt, Informatica, ADF, DataStage, Fivetran, Data Vault

Cloud Platforms: Azure (Data Factory, Synapse, Databricks), GCP (BigQuery, Dataflow, Cloud Storage), AWS (EC2, S3, CloudWatch, Sagemaker, EMR, Lambda)

Programming & Query Languages: Python, SQL(Advanced), TSQL, Scala, Go, Java, Unix and Shell Scripting

Big Data Ecosystem: Apache Spark, Hadoop, Hive, Presto, Flink, Beam, Kafka, HDFS, Oozie, PySpark, PyTorch

DevOps & IaC: Docker, Kubernetes, Jenkins, Terraform, GitHub, Azure DevOps, Agile, Datadog

Data Warehousing: Snowflake, Azure SQL DB, Cloud SQL, BigQuery, NoSQL (MongoDB, HBase), Postgre SQL, Kimball, DynamoDB, Medallion architecture.

Data Governance & Security: GDPR, HIPAA, CCPA, Role-based Access Control

Analytics & BI Tools: Tableau, Power BI, Mode, Pandas, Grafana, Qlik, NumPy, Lucid Chart, Microsoft 365, TensorFlow

PROFESSIONAL EXPERIENCE

Azure Data Engineer Santander Bank, TX Dec 2023 – Present

Designed and deployed scalable Azure Data Factory pipelines to automate ingestion and transformation of structured and semi-structured data from on-premise and cloud sources.

Developed complex SQL scripts, stored procedures, and partitioning strategies to support high-volume analytics in Azure Synapse.

Implemented CI/CD pipelines using Jenkins and Azure DevOps, automating deployments and version control for data workflows.

Enabled secure and compliant data operations with adherence to GDPR and CCPA, enhancing governance across sensitive datasets.

Optimized AKS (Azure Kubernetes Service) deployments for microservices architecture, increasing application uptime to 99.99%.

Collaborated with cross-functional Business Intelligence team to align data models with business requirements and reduce report latency by 35%.

GCP Data Engineer Royal Bank of Scotland India Mar 2021 – Nov 2022

Engineered data solutions using Google BigQuery, Cloud Dataflow, and Pub/Sub to build real-time data processing pipelines.

Orchestrated daily ingestion workflows using Apache Beam and Cloud Composer (Airflow on GCP), reducing manual intervention by 60%.

Built batch and streaming pipelines for financial transaction data, improving data pipeline reliability and throughput.

Integrated Sqoop with Cloud Dataproc to ingest legacy data into Hadoop clusters, reducing processing time by 30%.

Conducted performance tuning on Cloud SQL and BigQuery to support analytical queries over billions of records.

Data Engineer Qualcomm, India Jun 2019 – Feb 2021

Developed scalable ETL jobs using PySpark and HiveSQL, handling multi-terabyte datasets and achieving 99.9% data integrity.

Migrated on-prem pipelines to AWS cloud infrastructure using Terraform, increasing environment provisioning speed by 50%.

Deployed Docker containers orchestrated with Kubernetes, reducing infrastructure costs and improving system scalability.

Implemented monitoring and alerting via ELK Stack, CloudWatch, and Nagios, achieving 99.95% system availability.

Automated data preprocessing and transformations using NumPy and Pandas, improving pipeline run times by 30%.

PROJECTS

Student Mental Health Risk Prediction (Python, Scikit-learn, Pandas)

Developed a predictive ML model using Random Forest with 84% accuracy, analyzing student data to identify mental health risk factors.

Cleaned, engineered, and visualized features using Python, supporting timely academic interventions.

Life Expectancy Analytics Dashboard (Power BI, Excel, DAX)

Built a Power BI dashboard analyzing global life expectancy trends.

Cleaned and transformed raw datasets and applied DAX measures to uncover regional health disparities.

EDUCATION

Master of Science – Business Analytics University of North Texas Jan 2023 – May 2024

Related Coursework: Business Process Analytics, Predictive modelling, Data Mining, Programming Languages for BA

CERTIFICATIONS

Introduction to Python – Penn Engineering (University of Pennsylvania)

Databricks Accredited Generative AI Fundamentals

AWS Certified Solutions Architect – Associate (In Progress)

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