Senior Data Engineer with Cloud Data Pipelines expertise

Manasa G

Email: ****************@*****.***

Mobile: 937-***-****

LinkedIn: www.linkedin.com/in/manasagunreddy25

Senior Data Engineer

PROFESSIONAL SUMMARY

Data Engineer with 5+ years of experience designing, developing, and optimizing scalable data pipelines, ETL/ELT workflows, and cloud-native architectures across GCP, AWS, and Azure ecosystems.

Expertise in data warehousing and lakehouse solutions using BigQuery, Redshift, Synapse, and Delta Lake, enabling high-performance analytics and cost optimization.

Hands-on experience in real-time streaming pipelines with Pub/Sub, Kinesis, and Event Hub, supporting event- driven architectures and low-latency analytics.

Skilled in SQL, Python, and PySpark for large-scale transformations, advanced partitioning, and performance tuning across structured and semi-structured datasets.

Strong background in orchestration and automation using Airflow, Cloud Composer, Azure Data Factory, and CI/CD pipelines, improving reliability and reducing manual effort.

Adept at collaborating with cross-functional teams to modernize legacy systems, implement governance & security frameworks (IAM, Key Vault, KMS, Cloud Monitoring), and deliver actionable insights that drive business outcomes.

Guided teams to enhance collaboration and boost productivity through effective leadership skills.

Mentored team members to resolve conflicts and improve teamwork in high-pressure situations. TECHNICAL SKILLS

Cloud And Data Platforms - Microsoft Azure (ADF, Databricks, Synapse, Event Hub, ADLS Gen2, Microsoft Fabric), Amazon Web Services (Glue, Redshift, S3, Lambda, Kinesis, EMR, Athena), Google Cloud Platform

(BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage, Cloud Composer)

Databases And Warehousing - Snowflake, Azure Synapse, Redshift, BigQuery, Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, DynamoDB, Cosmos DB

Programming And Frameworks - Python (PySpark, Pandas, NumPy), Scala, SQL (T-SQL, PL/SQL), Shell Scripting, Spark (Batch & Streaming), Hadoop Ecosystem, PL-SQL

Data Engineering And Etl - Metadata-driven pipelines, Bronze–Silver–Gold architecture, Real-time Streaming, ELT/ETL workflows, Airflow, Cloud Composer, Data Fusion, ETL tools, data integration pipelines

Devops And Orchestration - CI/CD (Azure DevOps, AWS CodePipeline, GCP Cloud Build), Docker, Kubernetes

(AKS, EKS, GKE), Terraform, Git, automation pipeline management, OpenShift

Visualization And Bi - Power BI, Tableau, Looker Studio, QuickSight, Tableau Prep

Security And Governance - IAM (Azure AD, AWS IAM, GCP IAM), Key Vault, KMS, CloudWatch, Cloud Monitoring, Data Catalog, Data Governance & Compliance (HIPAA, GDPR, CCPA)

Data Science And Analytics Tools - Alteryx, RapidMiner

Software Architecture - large-scale architecture initiatives, enterprise rollouts

System Administration And Infrastructure - containers, containerized deployments

Technical Support And Troubleshooting - troubleshoot, resolve performance issues PROFESSIONAL EXPERIENCE

HCA Healthcare Dec 2023 – Present

Senior Data Engineer

Designed and implemented scalable ETL/ELT pipelines using AWS Glue and EMR (Spark) to process large volumes of healthcare claims, patient, and provider data with high accuracy.

Built and optimized data lakes and warehouses on Amazon S3, Redshift, and Athena, enabling secure storage and faster analytical queries for regulatory and clinical reporting.

Developed real-time data ingestion pipelines using Kinesis Data Streams, Firehose, and Lambda, delivering low- latency insights for patient monitoring and operational dashboards.

Applied data quality, compliance, and governance frameworks (HIPAA, GDPR, Lake Formation) to ensure secure handling of PHI/PII and adherence to healthcare regulations.

Automated infrastructure deployment using Terraform and CloudFormation, streamlining provisioning of serverless and containerized workloads across AWS accounts.

Partnered with healthcare analysts and stakeholders to deliver self-service analytics with Redshift, QuickSight, and Python, improving decision-making and reducing report generation time by 40%.

Led data preparation and integration efforts, enhancing data accuracy by 25% and streamlining data workflows for improved business intelligence.

Implemented workflow automation and architecture design, reducing manual processing time by 40% and increasing system reliability.

Developed data processing automation and performance optimization solutions, improving data throughput by 30% and reducing latency.

Enhanced code quality and scalability, resulting in a 20% increase in application performance and supporting larger data volumes.

Generated operational insights through leadership skills, mentoring teams to drive data-driven decision-making across departments.

Guided teams in PL-SQL and Alteryx, optimizing database queries and data transformation processes, leading to a 15% increase in reporting efficiency.

Bharati AXA Life Insurance July 2022 – June 2023

Data Engineer

Designed and orchestrated end-to-end ETL/ELT pipelines in Azure Data Factory (ADF) with parameterization, dynamic pipelines, and metadata-driven frameworks to process diverse insurance data sources (claims, policies, customer records).

Built and optimized data lakehouse architectures using Azure Data Lake Storage Gen2 (ADLS) and Delta Lake, implementing bronze–silver–gold zones to support lineage, governance, and high-performance analytics.

Developed advanced data models in Azure Synapse Analytics leveraging partitioning, materialized views, and indexing, reducing policy and claims reporting time by 40%.

Implemented real-time ingestion pipelines using Azure Event Hub and Stream Analytics, integrated with Databricks (PySpark/Scala) for streaming transformations and pushing enriched datasets into Synapse and Power BI dashboards.

Applied data governance, monitoring, and security controls using Azure Purview, RBAC, and Key Vault, ensuring compliance with insurance industry regulations and data privacy (GDPR, HIPAA).

Collaborated with actuarial and underwriting teams to deliver self-service analytics in Power BI, improving risk analysis, claims forecasting, and customer insights for business stakeholders.

Utilized RapidMiner and Tableau Prep to streamline data visualization processes, improving analytical capabilities and reducing report generation time by 50%.

Deployed applications on OpenShift for containerized deployments, ensuring consistent performance and scalability across environments.

Designed and managed ETL tools and data integration pipelines, achieving seamless data flow and reducing data processing errors by 30%.

Led automation pipeline management and large-scale architecture initiatives, enabling faster deployment cycles and reducing time-to-market by 20%.

Oversaw enterprise rollouts and containers, enhancing deployment efficiency and maintaining high availability in production environments.

Commonwealth Bank June 2020 – June 2022

Data Engineer

Designed and implemented scalable ETL/ELT pipelines using Cloud Dataflow and Dataproc (Spark) to process high-volume transactional and customer data across multiple banking systems.

Developed and optimized data warehouses and lakehouses using BigQuery and Cloud Storage, applying clustering and partitioning strategies to reduce query costs and improve performance by 35%.

Built real-time streaming pipelines leveraging Pub/Sub and Dataflow, enabling fraud detection, transaction monitoring, and low-latency analytics across critical banking applications.

Automated orchestration and scheduling with Cloud Composer (Airflow) to streamline workflows for compliance reporting, credit risk analysis, and regulatory audits.

Implemented governance, monitoring, and security frameworks using IAM, Cloud Monitoring, Cloud KMS, and Data Catalog, ensuring compliance with PCI DSS and banking data privacy regulations.

Partnered with data analysts and risk management teams to integrate Looker and BigQuery ML into workflows, enabling predictive analytics for loan default risk, customer segmentation, and portfolio optimization.

Troubleshot and resolved performance issues, achieving a 35% improvement in system response times and user satisfaction.

Coordinated scrum teams in enterprise-scale data initiatives, fostering collaboration and delivering projects on time and within budget.

Architected enterprise-level data solutions in a shared services environment, ensuring data consistency and accessibility across business units.

Spearheaded cross-functional initiatives and enterprise-level governance, aligning data strategies with organizational goals and improving compliance.

Optimized task dependency tuning, resulting in a 25% reduction in processing times and increased system throughput.

EDUCATION

Master’s in computer science - Wright State University

Bachelor’s in Electronics and communication engineering - Tkr college of engineering and technology

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