Avula Dileep

As an Azure Data Engineer, I am a highly logical and pragmatic professional, deeply committed to accountability and reliability in delivering robust data solutions. My ambition drives me to meticulously pursue mastery in crafting efficient architectures, ensuring every project reflects my dedication to high-quality, dependable results.

Open to

Bangalore · Hyderabad · Chennai · India

Work style

Remote, Hybrid, On-site

Contact details — on requestProof of Work — on request

Experience

Azure Data Engineer

Jeanmartian Systems India Pvt Ltd · Present

Not yet confirmed

Azure Data Engineer

Jeanmartian Systems India Pvt Ltd · Oct 2025 – Present

Not yet confirmed

Designed and orchestrated scalable Azure Data Factory pipelines to ingest data from SQL Server and flat files for high-volume airline credit card transactions and travel accommodation payments.
Built and optimized batch data processing workflows to handle large-scale financial transaction datasets with a focus on reliability and performance.
Implemented Azure Synapse pipelines for orchestration and analytics loading, supporting near real-time reporting needs.
Developed data validation and reconciliation logic (data quality checks) to ensure data accuracy and integrity across pipelines.
Created reusable, modular pipeline designs and maintained technical documentation and operational runbooks.
Collaborated with business and technical stakeholders to translate requirements into scalable data solutions.

Data Engineer

Jeanmartain systems india pvt ltd · Oct 2025 – Present

Not yet confirmed

Hi!
My name is Avula Dileep, and I’m an Azure Data Engineer with 5+ years of experience building scalable data solutions using Azure Data Factory, Databricks (PySpark), and Synapse Analytics.
I’m passionate about designing secure, production‑ready pipelines and optimising big data workflows.
I’m excited about work in payments and financial technology, and I’d love to explore how my skills in cloud data engineering and analytics can contribute to your mission.

Azure Data Engineer

TCS Pvt Ltd · Jan 2021 – Aug 2025

Not yet confirmed

Designed and developed end-to-end ETL/ELT pipelines using Azure Data Factory, Azure Databricks, and Microsoft Fabric Data Factory to ingest and process structured and semi-structured data.
Built scalable Spark-based data processing workflows using PySpark, including joins, aggregations, and conditional transformation logic; tuned Spark jobs for performance on large datasets.
Implemented Medallion Architecture (Bronze, Silver, Gold) using Delta Lake and optimised Lakehouse tables in Azure Databricks, Azure Synapse Analytics, and Microsoft Fabric Lakehouse environments.
Developed and managed Microsoft Fabric Lakehouses and leveraged OneLake as a centralized data storage layer for analytics and reporting.
Configured Azure Logic Apps for automated alerts and notifications across pipeline workflows.
Migrated legacy on-premises ETL systems (SSIS) to Azure Cloud, modernising data infrastructure.
Optimised SQL/T-SQL queries and pipeline performance; integrated data from SQL Server, CSV, Parquet, and flat file sources.

Azure Data Engineer

INTENSO TECH SOLUTION PRIVATE LIMITED · Jan 2021 – Aug 2025

Not yet confirmed

Highlights
• Designed and developed end-to-end data engineering solutions using Azure Data Factory, Azure Databricks, PySpark, SQL, Azure Synapse Analytics, and Microsoft Fabric.
• Built scalable ETL/ELT pipelines for large-scale structured and semi-structured data across Insurance, Healthcare, and Travel & Payments domains.
• Implemented Medallion Architecture (Bronze, Silver, Gold) using Delta Lake and Lakehouse architectures for reliable and analytics-ready data.
• Developed PySpark-based data transformation workflows involving joins, aggregations, filtering, cleansing, and business-rule implementation.
• Implemented incremental and CDC-based data ingestion strategies to efficiently process changing source data.
• Migrated legacy on-premises SSIS workflows to modern Azure cloud-based data pipelines.
• Developed data quality, validation, reconciliation, and anomaly-detection frameworks to improve data accuracy and reliability.
• Optimized SQL queries, Spark jobs, Delta Lake tables, partitioning strategies, and Azure pipelines for improved performance and resource efficiency.
• Built and supported analytics-ready datasets for Power BI and business reporting requirements.
• Worked with SQL Server, CSV, Parquet, flat files, Azure Data Lake Storage, Synapse, and Microsoft Fabric Lakehouse environments.
• Implemented pipeline monitoring, error handling, retry mechanisms, automated alerts, and operational documentation to improve data platform reliability.
• Collaborated with business, technical, finance, clinical, and compliance stakeholders to translate requirements into scalable data solutions.

Skills 0 proven through work

Also works with

Technical ContributionSemi-structured Data HandlingIncremental Data ProcessingReal-time Reporting System DevelopmentData Pipeline ParameterizationCode ReusabilityData Availability ManagementTravel Industry KnowledgeFintech Domain KnowledgeHealthcare Domain KnowledgeAzure DeploymentCI/CD Pipeline ImplementationSelf-Directed LearningAzure AI Services IntegrationMicrosoft Fabric UsagePreventive Measures PlanningProduction Environment SupportData GovernanceCross-Departmental CoordinationStakeholder Communication AdaptationData Partitioning and Segregation DesignFunctional TestingApplication DeploymentDependency AnalysisSystem AnalysisAdaptabilityWork Planning and PrioritizationMentoring and Peer CoachingLegacy System MigrationApplication Performance OptimizationTaking OwnershipProcessing Pipeline OptimizationData MonitoringBusiness IntelligenceTeamworkHadoop UsageData ProvisionArchitectural DesignRequirements AnalysisTechnical TroubleshootingETL TestingScalable System DesignData Discrepancy InvestigationData QuarantiningData Unification and NormalizationSchema Drift ManagementTabular Data Cleaning & ValidationDatabase Query OptimizationMedallion Architecture DesignDelta Live Tables UsageInput Validation ImplementationApache Airflow OrchestrationData HandlingPySparkDatabricks UsageData ModelingBug FixingRoot Cause AnalysisReliability ImprovementSOP DevelopmentTechnical DocumentationData CurationAzure Synapse Analytics UsageStructured LoggingError HandlingRetry Logic ImplementationData Repetition PreventionData TransformationData ValidationData EngineeringAzure Data Lake UsageETL Pipeline DevelopmentAzure Data Factory Pipeline DevelopmentAnalytics Layer ArchitectureData LoadingWorkflow Design (Process Mapping)Transaction ReconciliationAnalytical Report CreationData PreprocessingData Integrity ManagementWorking with CSV Files

Proof of Work

Avula shares this with people who ask. You'll hear back either way.

Links

linkedin.com/in/dileep-avula-a6b85540a

Contact details

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