Rakesh Vishwabrahmana

Data Engineer

London, England, United Kingdom8 yrs 10 mos experience

Highly StableAI Enabled

Key Highlights

Expert in architecting scalable data pipelines on Azure.
Proven track record in automating CI/CD processes.
Strong experience in real-time data ingestion frameworks.

Stackforce AI infers this person is a Data Engineer specializing in SaaS solutions with a focus on Azure technologies.

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Skills

Core Skills

Microsoft AzureData EngineeringMicroservices ArchitectureDevopsData MigrationData Analysis

Other Skills

ADLS Gen2AI SearchAPI TestingArgoCDAzure ADAzure Data FactoryAzure DatabricksAzure DevOpsAzure Event HubsAzure FunctionsAzure OpenAIAzure SQL DBAzure SQL MIContinuous Integration and Continuous Delivery (CI/CD)Cybersecurity

About

Experienced Data Engineer specialising in Azure and Microsoft Fabric ecosystems, with strong capabilities in architecting scalable data pipelines, lakehouse-based designs and real-time ingestion frameworks using Azure Data Factory (ADF) and modern cloud-native services. Skilled in engineering reliable, secure and high-performance data workflows, applying best practices in governance, data quality and DevOps automation. Hands-on experience building cloud APIs with FastAPI, front-end interfaces using Angular/TypeScript, and integrating advanced Azure AI and LLM capabilities to enhance analytical and operational value. Proficient in Docker and Kubernetes for container orchestration and deployment of scalable microservices. Proven ability to solve complex data challenges, optimise pipelines and deliver robust, production-ready solutions across large enterprise environments.

Experience

8 yrs 10 mos

Total Experience

5 yrs 3 mos

Average Tenure

3 yrs 7 mos

Current Experience

Crowe uk

Data Engineer

Nov 2022 – Present · 3 yrs 7 mos · Greater London, England, United Kingdom · Hybrid

Designed and implemented end-to-end Azure-based data platforms using Azure Data Factory, Azure Databricks, ADLS Gen2, Azure SQL MI, and Microsoft Fabric, supporting enterprise-scale reporting and advanced analytics workloads.
Developed containerised microservices using FastAPI, Docker, and Kubernetes (AKS), enabling scalable API-driven data ingestion and metadata services.
Built interactive Angular + TypeScript applications to support operational dashboards, data validation workflows, and admin interfaces for internal users.
Developed and maintained highly available real-time streaming pipelines using Azure Event Hubs, Structured Streaming, and Azure Functions to ingest, transform, and serve time-sensitive datasets.
Automated CI/CD pipelines using Azure DevOps, GitHub Actions, YAML pipelines, and Terraform, enabling seamless deployment of Databricks notebooks, FastAPI microservices, Fabric assets, and Kubernetes workloads.
Implemented GitOps workflows with ArgoCD and Helm charts, standardising deployment processes and reducing configuration drift across cloud environments.
Secured AKS clusters with RBAC, Azure AD integration, Pod Identity, Network Policies, and TLS/SSL termination using NGINX Ingress Controller to ensure compliance with organisational security standards.
Designed and deployed Fabric Data Pipelines & Dataflows Gen2, modernising legacy ETL systems and reducing pipeline execution time by 35%.
Built LLM-based RAG pipelines using Azure OpenAI, AI Search, and embedding generation, enhancing enterprise document discovery and semantic search by 35%.
Migrated on-prem SQL Server and DB2 systems to Azure SQL MI and ADLS Gen2, achieving 99% data accuracy and reducing migration timelines by 20%.
Partnered with cross-functional stakeholders, data architects, and business teams to define data ingestion standards, platform requirements, and governance frameworks.

Azure Data FactoryAzure DatabricksADLS Gen2Azure SQL MIMicrosoft FabricFastAPI+18

Wipro

2 roles

Data Engineer

Promoted

Sep 2019 – Aug 2022 · 2 yrs 11 mos · Hyderabad, Telangana, India

Developed scalable ETL/ELT pipelines using Azure Data Factory, Databricks, Python, SQL, and Azure SQL DB to support enterprise reporting and analytics.
Automated business-critical reports using Python and SQL, improving reporting accuracy by 30% and reducing manual intervention.
Built data ingestion solutions using Azure Event Hubs and Azure Functions, enabling near real-time processing and alerting for operations teams.
Worked closely with data scientists to design and deploy predictive models using MLflow, Scikit-learn, and Azure Databricks.
Designed and maintained Power BI datasets and dashboards, supporting business units with self-service analytics capabilities.
Utilised Azure Key Vault, RBAC, and encryption standards to secure sensitive data assets and ensure governance compliance.
Implemented Infrastructure-as-Code using Terraform to automate provisioning of ADF, Databricks, Storage, Key Vault, and SQL resources.
Optimised SQL queries, stored procedures and indexing strategies in Azure SQL DB and SQL Server to improve performance across reporting workloads.
Participated in agile development ceremonies, gathering requirements, defining acceptance criteria and delivering solutions iteratively.

Azure Data FactoryDatabricksPythonSQLAzure SQL DBAzure Event Hubs+7

Data Analyst

May 2017 – Sep 2019 · 2 yrs 4 mos · Hyderabad, Telangana, India

Designed and developed a centralised SQL Server data warehouse, improving organisational data accessibility by 40% and accelerating reporting cycles by 35%.
Built intuitive Power BI dashboards enabling leadership teams to track KPIs, operational metrics and campaign insights.
Conducted in-depth data analysis using Python (Pandas, NumPy), SQL and statistical methods to identify business trends and actionable improvements.
Automated validation scripts using Python and SQL, improving data accuracy by 25% and reducing manual data checks.
Built logging, monitoring and alerting solutions using Prometheus, Grafana, Azure Monitor, and Log Analytics, improving system uptime and reducing resolution time by 30%.
Supported data governance efforts by documenting data dictionaries, lineage, and quality rules across multiple business systems.

SQL ServerPower BIPythonPandasNumPyPrometheus+3