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Azure Data Factory, Databricks, Microsoft Fabric and Snowflake pipelines — plus the Power BI layer on top. SAP, Epicor, Salesforce and NetSuite already synced to Azure. 5+ years in Azure data engineering. I scope, build and hand over the whole path: source system → ingestion → ETL/ELT into a Medallion Lakehouse (Bronze, Silver, Gold) → semantic model → the dashboard your team actually opens. Most projects reach me one of four ways: - No data platform yet — spreadsheets, an app database, and numbers people need every week - A legacy platform that needs moving to Microsoft Fabric, Azure or Databricks - An ERP or CRM that won't talk to your warehouse — SAP, Epicor, Salesforce, NetSuite and QuickBooks are ones I've already wired to Azure - Month-end reporting that takes three days and still doesn't reconcile 🔧 What I build ✅ New data platforms from scratch — empty Azure subscription to first working dashboard ✅ Azure Data Factory and Microsoft Fabric pipelines — OneLake, Lakehouse, Warehouse, Notebooks ✅ Azure Databricks, Apache Spark and Delta Lake processing at scale ✅ ETL and ELT development, including incremental and metadata-driven patterns ✅ Data warehouses, Lakehouse architectures and dimensional data models ✅ API, ERP, CRM and SQL database integrations ✅ Legacy platform migrations to Microsoft Fabric, Azure and Databricks ✅ Power BI dashboards, semantic models and DAX ✅ Data quality, validation, monitoring, and cost and performance tuning 🛠️ Stack Microsoft Fabric · Azure Data Factory · Azure Databricks · Azure Synapse Analytics · Azure SQL Database · Snowflake · BigQuery · SAP Python · SQL · PySpark · DAX SQL Server · PostgreSQL · MySQL Power BI · Tableau · Looker Studio 🤝 How I work ✅ A written build plan before any code — scope, sequence, and what "done" means ✅ Pipelines ship with logging and failure alerts, not just a green run on my machine ✅ Handover documentation, so your team can run it without me ✅ 4+ hours of daily overlap with US business hours (I'm UTC+5:30) 📩 Send me your source list and the one report that keeps breaking. I'll come back with a pipeline plan, a rough timeline, and an honest answer about whether Microsoft Fabric is the right target for you.

I am a senior Data Engineer with 6+ years of experience designing and building large-scale data pipelines and analytics platforms across finance, consulting, and enterprise domains. Currently working as a Sales Data Analytics Engineer at Russell Investments, I design and maintain high-performance data pipelines processing millions of records daily using Python, Pandas, Polars, Spark, and Snowflake. I have strong experience in building end-to-end ETL/ELT systems, optimizing SQL for sub-second query performance, and automating workflows using Apache Airflow and CI/CD. Previously at Cognizant, I built real-time and batch data platforms using Kafka, AWS Glue, S3, Snowflake, and Vertica, handling 10M+ records daily and achieving 99.9% pipeline reliability. I specialize in data modeling, performance tuning, cost optimization, and building production-grade analytics systems. Core expertise: • Data Warehousing: Snowflake, Vertica, SQL Server • ETL & Orchestration: Airflow, AWS Glue, Control-M • Big Data: Spark, Kafka, PySpark • Programming: Python, SQL (Advanced), Pandas, Polars, NumPy • Cloud: AWS (S3, Redshift, Glue), CI/CD, Git • Data Modeling & Optimization What clients get when working with me: ✔ Scalable, reliable data pipelines ✔ Optimized Snowflake & SQL performance ✔ Clean, production-ready Python code ✔ Automated workflows with monitoring ✔ Clear communication and on-time delivery I help startups and enterprises with: End-to-end data pipeline development Snowflake & cloud data warehouse design SQL performance tuning Real-time & batch ETL systems Data migration & modernization Analytics-ready data models

👋 Hi, I’m Dharanish, a Senior Azure Data Engineer with 5+ years of hands-on experience delivering enterprise-grade data pipelines, cloud integrations, and BI solutions across Azure, AWS, and on-prem ecosystems. I help businesses build modern, automated data platforms using tools like Databricks, ADF, Synapse Analytics, and Power BI — transforming raw data into reliable, analytics-ready assets that drive smarter decisions and measurable results. ⚙️ Core Technical Expertise 1️⃣ Data Engineering & Architecture Architected Medallion Architecture (Bronze/Silver/Gold) using Databricks, Delta Lake, and Parquet for scalable, high-performance pipelines. Built ETL/ELT frameworks using Azure Data Factory, SSIS, Informatica, and Workato — integrating diverse data sources and automating end-to-end workflows. Designed batch and near-real-time pipelines using ADF, ADLS Gen2, and SQL Server, ensuring governance and lineage via Unity Catalog. 2️⃣ Programming & Data Transformation Expert in Python and PySpark for data transformation, schema validation, and performance tuning. Experienced in integrating Workato automation workflows for data movement, validation, and cross-platform triggers. 3️⃣ Cloud & DevOps Integration Skilled in Azure (ADF, Synapse, Logic Apps, Data Lake) and AWS (S3, RDS, EC2, IAM) for hybrid data architectures. Built and automated deployment pipelines using GitHub Actions and Azure DevOps CI/CD, ensuring reliable releases and rollback control. 4️⃣ Database & ETL Development Strong SQL, PL/SQL, and T-SQL expertise — query optimization, indexing, stored procedures. Developed and maintained SSIS and Informatica mappings for ETL workflows, implementing error handling, logging, and incremental load patterns. 5️⃣ Business Intelligence & Visualization Built Power BI dashboards and Excel-based analytics with DAX, drill-throughs, and KPIs for decision-making. Integrated Power BI with Azure Synapse and Databricks to create unified data visualization layers. 📊 🛠 Tech Stack & Tools ETL/ELT: Databricks | ADF | SSIS | Informatica | Workato | Synapse Analytics Programming: Python | PySpark | SQL | PL/SQL Cloud: Azure | AWS | ADLS Gen2 | Logic Apps BI & Visualization: Power BI | Excel | DAX | KPIs Testing: Postman | JMeter DevOps: GitHub | Azure DevOps | CI/CD | Agile | JIRA Other Tools: WordPress | PowerPoint | Excel Automation Thanks, DHARANISH S 🔹 Verified Rising Talent | 100% Job Success 📊 5-Star Power BI Deliverables | Azure Data Engineer

Microsoft Azure & Data Engineering I have extensive experience architecting and delivering production-ready data solutions within the Azure ecosystem and Microsoft Fabric. My background includes the end-to-end development of high-performance Lakehouse architectures, where I’ve utilized Fabric Pipelines and ADF to orchestrate complex data flows. I have a proven track record of provisioning secure infrastructure—from ADLS Gen2 to Azure SQL Databases—and building parameter-driven ingestion frameworks that handle diverse data sources. By integrating Logic Apps and WebHooks, I’ve successfully implemented automated monitoring systems that ensure 24/7 data availability and rapid incident response, providing a seamless flow from raw ingestion to analytics-ready Gold layers. Azure Databricks & Apache Spark I have a deep technical background in solving big data challenges using Azure Databricks and PySpark. I have successfully implemented Medallion Architectures (Bronze, Silver, Gold) to transform raw, unstructured data into optimized Delta tables for advanced analytics. By leveraging Analytical Functions and fine-tuning Spark cluster configurations, I have significantly reduced data processing windows for large-scale datasets. By optimizing cluster configurations and utilizing Analytical Functions, I significantly reduce processing windows and compute costs. I specialize in bridging the gap between raw data lakes and business intelligence, ensuring that data is partitioned, indexed, and optimized for downstream consumption. My focus is always on creating a high-performance "Single Source of Truth" that allows BI tools to pull insights with minimal latency. Informatica Intelligent Cloud Services (IICS) As an IICS Data Integration Specialist, I build high-concurrency ETL/ELT solutions that act as a bridge between diverse enterprise ecosystems. I have extensive experience developing complex mappings to extract high-volume data from Salesforce (SFDC), Oracle, and SQL Server, transforming it for delivery into Azure , AWS environments and Snowflake. My approach focuses on maximizing throughput and ensuring data integrity through advanced transformation logic, reusable mapping tasks, and standardized error-handling frameworks that support global business requirements. Informatica PowerCenter & Legacy Modernization With a deep background in Informatica PowerCenter, I specialize in the full SDLC of enterprise data warehousing, from star-schema design to production deployment. I have a proven track record of optimizing legacy workflows by re-engineering complex mappings and sessions using PL/SQL and Unix Shell Scripting for maximum efficiency. My core strength is modernizing these legacy footprints—moving global organizations from traditional on-premise ETL to agile, cloud-integrated architectures without interrupting business-critical operations. Multi-Cloud Data Engineering I have a proven track record of managing complex data ecosystems across Azure, AWS, and SaaS platforms (Salesforce/IICS). My approach is rooted in DataOps, where I automate the end-to-end orchestration of data pipelines to eliminate manual intervention and reduce human error. I have built resilient systems using configuration-driven triggers, cross-cloud authentication, and Unix scripting to ensure secure, seamless data flow between providers.

Dynamic QA Team Lead and worked as Scrum Master with 10 years of experience in quality assurance, test management, business analysis, and agile project delivery across Banking, Finance, Healthcare, Investments, Education, and Fitness domains. Proven track record of leading cross-functional teams, implementing robust QA processes, and driving continuous improvement initiatives. Adept at stakeholder management, requirements analysis, and mentoring teams to deliver high-quality software solutions. Also a certified fitness coach with a passion for coaching and personal development. Core Competencies: • QA Leadership & Team Management • Agile/Scrum Methodologies • Business Analysis & Stakeholder Management • ETL/DWH & Database Testing • API & Web Application Testing • Defect Management • Test Planning, Strategy & Execution • Reporting Tools (Power BI, OBIEE, Vermilion) • SQL, Informatica, Control-M, JIRA, Postman, Salesforce • Risk Management & Process Improvement • Effective Communication & Collaboration

I am 🏆 Certified Databricks (Associate ,Professional & GenAI) and 🏆 Microsoft Fabric & Azure Data Engineer with 8+ years of experience in ETL, leveraging Microsoft Azure technologies, Databricks, BigQuery, Microsoft Fabric, GCP, PySpark, SQL, MS SQL Server, Snowflake, and MySQL to deliver top-tier data solutions. My expertise spans a wide range of technologies and tools, ensuring seamless data movement, data scraping and transformation. I am skilled in orchestrating complex data workflows, automating pipelines, and streamlining ETL processes using AWS Glue, AWS EMR, Azure Data Factory, Databricks,Apache Airflow, SSIS Pentaho, Talend, Informatica etc. I excel at integrating with top-tier data warehouse platforms such as Snowflake, Redshift, Azure Synapse Analytics, and BigQuery, building robust ETL pipelines while managing data lakes on ADLS, S3, Databricks Lakehouse Platform and GCS. 🏆 Key Areas of Expertise: 📌 Development Skills: Databricks, Unity Catalog, Lakeflow, Kafka, Airflow, Airbyte, MS-SQL Server, Power BI, Tableau, Qlik, Apache Superset, Azure Data Factory, MySQL, ETL, Job Scheduling and Automation, Query Optimization etc. Performance Tuning 📌 Programming Languages: Python, SQL, PySpark 📌 Databases: SQL Server, PostgreSQL, MySQL, DynamoDB, Amazon RDS 📌 ETL Tools: AWS Glue, AWS EMR, Azure Data Factory, SSIS, Apache Airflow, Pentaho, Talend, Informatica. 📌 Data Scraping: Expertise in Python, Selenium, Playwright, Puppeteer and BeautifulSoup. 📌 Data Warehouse Platforms: Azure Synapse Analytics, Redshift, BigQuery, Snowflake 📌 Data Storage Services: Amazon S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS), Databricks File System (DBFS) 📌 Big Data Technologies: Hadoop, Hive, HBase 📌 Workflow Orchestration: Apache Airflow, Azure Data Factory 📌 Data Lake Management: Delta Tables, Delta Live Tables, Data Flows, Jobs 📌 Visualization Tools: Power BI, Tableau, Superset 📌 IDE’s: Databricks, SQL Server Management Studio, DBeaver, Snowflake, Azure Data Studio 📌 Cloud Platforms: Azure, GCP, AWS, Snowflake. Our comprehensive skill set, and hands-on experience make us adept at tackling any data engineering challenge thrown our way.