Senior Data Engineer - Cloud Data Platform Architect

Subhash Lakkamraju

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

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

Senior Data Engineer

PROFESSIONAL SUMMARY

Architected cloud data platforms for regulated enterprises, delivering reliable pipelines, governed warehouses, and analytics-ready datasets across Azure, AWS, and GCP production environments globally, securely.

Engineered batch and streaming ingestion with Spark, Airflow, Python, and SQL, improving data availability, quality validation, and reproducible transformations for downstream consumers daily, consistently.

Optimized warehouse performance and cost through partitioning, clustering, and workload tuning, enabling timely reporting, ad hoc exploration, and scalable self-service analytics for business stakeholders.

Standardized CI/CD, testing, and observability practices with Git and Jenkins, accelerating releases, strengthening lineage, and supporting cross-functional stakeholders with secure access documentation, reliably, compliance.

Facilitated team meetings using excellent written oral communication skills, enhancing collaboration and project alignment.

Implemented automation processes with passion automation continual process improvement, significantly boosting operational efficiency.

Enhanced ETL/database load/extract processes using Informatica within Agile methodology, resulting in a 30% reduction in data processing time and improved system reliability.

Redesigned ETL architecture and optimized pipes, achieving a 40% increase in data throughput and enhancing overall system scalability.

TECHNICAL SKILLS

Cloud Platforms - AWS (EC2, Lambda, Glue, S3, Kinesis, IAM, EKS, Redshift), Azure (ADF, Synapse, Azure SQL, Entra ID, Key Vault), GCP (BigQuery, GKE, Cloud Storage), Microsoft Fabric

Infrastructure as Code (IaC) - Terraform, Ansible, ARM Templates, Bicep, CloudFormation, Jenkins, Azure DevOps

Monitoring and Incident Response - New Relic, AWS CloudWatch, Azure Monitor, ServiceNow, RCA, SLA Management

Security and Compliance - IAM, Encryption, NIST 800-53, CIS Benchmarks, PCI-DSS, RBAC, Key Vault, Audit Logging

CI/CD and DevOps - Jenkins, GitHub Actions, Git, GitLab, CodePipeline, CI/CD Pipelines, Shell Scripting Programming & Scripting - Python, SQL, Bash, PowerShell

Data Engineering - AWS Glue, Azure Data Factory, DBT, Apache Kafka, Spark, Hive, GCP Dataflow, ETL, data warehouses, data flows

Databases - Redshift, Snowflake, Azure SQL, PostgreSQL, MongoDB, MySQL, Oracle, Oracle Exadata

Dashboards and Visualization - Power BI, Tableau, Looker, AWS QuickSight

Programming Languages - Perl

Tools and Platforms - Informatica

System Administration - Linux-based processes, Linux environment setup, Unix file systems, mount types, permissions, standard tools, pipes

PROFESSIONAL EXPERIENCE

McKesson June 2025 – Present

Sr. Data Engineer

Architected Azure Databricks Delta Lake medallion layers on ADLS Gen2, standardizing bronze-to-gold transformations and enabling consistent clinical analytics across enterprise datasets for scalable reporting.

Orchestrated Azure Data Factory pipelines with dependency checks, triggers, and retries, meeting SLAs and delivering reliable daily refreshes for operational and executive reporting consistently.

Engineered HL7 and FHIR ingestion with Event Hubs, Azure Functions, and Databricks, normalizing near real time patient events and improving interoperability for care-management analytics products.

Optimized Azure Synapse dedicated SQL pools with partitioning, distribution choices, and workload management, accelerating dashboards and reducing query latency for supply chain users significantly.

Standardized CI/CD with Azure DevOps, integrating notebook validation, ARM/Bicep deployments, and release gates to accelerate safe production rollouts across data platforms with automated approvals.

Automated environment provisioning via ARM templates and Azure Policy, ensuring repeatable builds and preventing configuration drift across dev, test, and production subscriptions enterprise-wide securely.

Secured secrets using Azure Key Vault, managed identities, and private endpoints, preventing credential exposure and enforcing compliant access to HIPAA-regulated PII datasets across environments.

Cataloged datasets and lineage in Microsoft Purview, improving discovery, stewardship, and audit readiness while enabling governed self-service access across McKesson teams for trusted decisions.

Enhanced system/architecture improvements by utilizing Data Warehousing and Perl, resulting in 30% reduction in data retrieval time.

Optimized data warehouses and data flows with Backend Focus, achieving 40% increase in data processing throughput.

Streamlined Linux-based processes through Linux environment setup and orchestration tools, enhancing system reliability by 25%.

PNC Financial Services April 2024 – May 2025

Data Engineer

Engineered S3 landing and Glue catalog pipelines, transforming card and ACH transactions with EMR Spark, delivering curated risk tables for analysts daily enterprise-wide consistently.

Automated incremental ingestion with AWS DMS and Glue jobs, merging CDC changes into S3 curated zones and reducing reconciliation effort monthly for audits significantly.

Standardized infrastructure provisioning through Terraform and CloudFormation, parameterizing VPC, subnets, and IAM policies to deliver repeatable multi-account deployments across regions securely with versioned modules.

Optimized EMR Spark workloads by tuning partitions, broadcast joins, and executor sizing, cutting runtime and controlling compute spend during peak batches each quarter reliably.

Monitored pipelines using CloudWatch metrics, logs, and alarms, diagnosing failures quickly and improving SLA adherence for daily warehouse refreshes for business reporting users internally.

Secured data lake access with KMS encryption, key rotation, and least-privilege IAM roles, enabling compliant sharing with auditors and partners across regulated datasets safely.

Implemented Airflow scheduling with retries, backfills, and alerting, ensuring batch dependencies completed on time and meeting cutoff windows daily during market volatility periods too.

Governed dataset quality by enforcing schema checks, unit tests, and reconciliation queries, preventing downstream fraud-score distortions and improving trust among risk leadership teams weekly.

Leveraged Oracle Exadata and Oracle to boost data query performance, reducing latency by 35%.

Integrated Oracle with Perl, achieving 20% improvement in script execution efficiency. Accenture October 2019 – September 2022

Data Engineer

Designed GCP ingestion on Cloud Storage and Pub/Sub, processing events with Dataflow to populate BigQuery for near real-time executive analytics globally securely at scale.

Constructed ELT pipelines with dbt and BigQuery SQL, producing certified marts and reusable metrics layers that aligned KPIs across domains for stakeholders monthly reviews.

Modeled dimensional schemas in BigQuery, applying partitioning and clustering to reduce scan costs and accelerate ad hoc analysis for teams across multiple client programs.

Developed Dataflow streaming jobs with Beam, handling late data and deduplication to deliver accurate operational dashboards for leadership in hours not days anymore consistently.

Validated data quality through dbt tests, BigQuery assertions, and anomaly checks, catching issues early and preventing inconsistent definitions in reports for regulated metrics tracking.

Integrated Tableau and Power BI with BigQuery semantic views, enforcing row-level security and enabling governed self-service exploration for business users across global delivery teams.

Automated CI/CD via Cloud Build and Git, deploying dbt artifacts and Dataflow templates reliably, reducing manual promotion steps for releases into production each sprint.

Documented lineage and governance in Data Catalog and IAM policies, improving dataset discoverability and audit readiness for client compliance engagements through standard access reviews.

Configured Unix file systems and mount types, leading to a 15% increase in data access speed.

Utilized standard tools to manage permissions, resulting in a 20% increase in system security compliance. EDUCATION

Master's in Business Analytics - St. Francis College

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