Hire the Best DataCulture Velo Specialists

¸¸♬·¯·♪·¯·♫¸¸ 𝗪𝗲𝗹𝗰𝗼𝗺𝗲 𝘁𝗼 𝗺𝘆 𝗽𝗿𝗼𝗳𝗶𝗹𝗲! ¸¸♫·¯·♪¸♩·¯·♬¸¸ I'm a Senior Data Engineer & Cloud Data Architect. I bridge the gap between fragmented raw data and high-performance, analytics-ready infrastructure. Whether you need to build a scalable data warehouse from scratch, transition from legacy ETL to modern dbt/Databricks stack, optimize costly cloud queries, or power real-time AI/ML applications, I specialize in architecting reliable, zero-downtime data pipelines across AWS, GCP, Azure, Snowflake, and BigQuery. ⚡ 𝐂𝐨𝐫𝐞 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 1. End-to-End Modern Data Stack (MDS) & ETL/ELT Pipelines Designing and deploying automated, resilient pipelines that extract, clean, transform, and load petabyte-scale data into centralized analytics hubs. ◾ Batch & Stream Ingestion: Building automated ingestion jobs from SaaS applications, REST APIs, webhooks, and legacy DBs using Fivetran, Airbyte, Kafka, and Debezium (Change Data Capture - CDC). ◾ Analytics Engineering: Modular, version-controlled transformations with dbt (Data Build Tool), custom SQL, and PySpark-complete with automated documentation and lineage tracking. ◾ Workflow Orchestration: Designing DAGs, automated retries, and monitoring alerts using Apache Airflow, Prefect, Dagster, and AWS Step Functions. 2. Cloud Data Warehousing & Lakehouse Architecture (Snowflake, Databricks, BigQuery) Structuring high-efficiency, cost-optimized databases designed for instant analytical querying and BI dashboard performance. ◾ Warehouse Optimization: Clustering keys, partitioning, materialization, micro-partitioning, and query tuning to cut monthly cloud compute/storage costs by 30%–60%. ◾ Lakehouse & Open Table Formats: Architecting Delta Lake, Apache Iceberg, and Hudi layers on AWS S3/GCP Cloud Storage using Medallion Architecture (Bronze -> Silver -> Gold). ◾ Data Modeling: Dimensional modeling (Kimball methodology), Star/Snowflake Schemas, Data Vault 2.0, and Wide Flat Tables (OBT) optimized for Looker, Tableau, and PowerBI. 3. Real-Time Data Streaming & Event-Driven Systems Enabling millisecond-latency processing for live dashboards, fraud detection, dynamic pricing, and real-time operational metrics. ◾ Event Streaming: Setting up Apache Kafka clusters, AWS Kinesis, GCP Pub/Sub, and RabbitMQ with event serialization (Avro, Protobuf). ◾ Real-Time Analytics: Developing continuous stream-processing engines using Apache Flink, Spark Streaming, and ClickHouse/RisingWave for immediate insight delivery. 4. Data Quality, Governance, MLOps & AI Infrastructure Ensuring every byte of data entering your reporting systems is accurate, secure, compliant, and ready for advanced analytics or LLM applications. ◾ Data Quality & Observability: Automated schema validation, anomaly detection, and data testing using Great Expectations, Soda, and dbt test suites. ◾ AI/ML Infrastructure: Vector database setup (Pinecone, Weaviate, Qdrant, Milvus), RAG pipeline data ingestion, and feature store integration (Feast) for AI model training. ◾ Governance & Compliance: Role-Based Access Control (RBAC), Column/Row-level masking, PII obfuscation, and automated lineage mapping for GDPR/HIPAA compliance. ⚡ 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 & 𝐅𝐫𝐚𝐦𝐞𝐰𝗼𝗿𝐤𝐬 𝐈 𝐇𝗮𝘃𝐞 𝐌𝐚𝐬𝐭𝐞𝐫𝐞𝐝 - 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Apache Airflow, Prefect, Dagster, Mage, AWS Step Functions, MWAA - 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗲𝘀 & 𝗘𝗻𝗴𝗶𝗻𝗲𝘀: Snowflake, Google BigQuery, AWS Redshift, ClickHouse, Trino/Presto, DuckDB - 𝗗𝗮𝘁𝗮 𝗟𝗮𝗸𝗲 / 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲: Databricks, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue, PySpark, Apache Spark - 𝗘𝗧𝗟 / 𝗘𝗟𝗧 & 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: dbt (Core & Cloud), Airbyte, Fivetran, Kafka Connect, Debezium, Meltano - 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 & 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴: Apache Kafka, AWS Kinesis, GCP Pub/Sub, Apache Flink, Spark Streaming, RabbitMQ - 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 (𝗡𝗼𝗦𝗤𝗟 & 𝗥𝗗𝗕𝗠𝗦): PostgreSQL, MySQL, MongoDB, Redis, Cassandra, DynamoDB, Pinecone, Qdrant - 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 & 𝗦𝗾𝗹: Python (Pandas, Polars, PySpark, SQLAchemy), SQL (Advanced Dialects), Scala, Bash, Go - 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 & 𝗗𝗲𝘃𝗢𝗽𝘀: Terraform, Docker, Kubernetes, AWS (S3, EC2, ECS, Lambda), GCP, Azure, GitHub Actions, CI/CD - 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 & 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Great Expectations, Soda, Monte Carlo, OpenLineage, Datahub ⚡ 𝗛𝗼𝘄 𝗜 𝗪𝗼𝗿𝗸: I am hired to design production-grade data pipelines, modernize legacy data stacks, fix slow analytics queries, and bring software engineering best practices (Git, CI/CD, unit testing, modular code) into data infrastructure. I prioritize clean lineage, cost efficiency, ironclad data security, and zero-downtime migrations. ⚡ 𝗪𝗵𝘆 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗖𝗵𝗼𝗼𝘀𝗲 𝗠𝗲: ✔️ Pipelines built to scale ✔️ Massive cloud bill reduction ✔️ Production-grade reliability ✔️ Software engineering rigor ✔️ Clear communication 👉 𝗖𝗹𝗶𝗰𝗸 𝗠𝗲𝘀𝘀𝗮𝗴𝗲 - 𝗹𝗲𝘁'𝘀 𝘁𝗮𝗹𝗸.

I am a Data Engineer with strong experience building end-to-end data pipelines, cloud data architectures, and automated analytics systems. I specialize in developing scalable ELT/ETL workflows using tools such as Airflow, dbt, Docker, Snowflake, PostgreSQL, MySQL, and AWS, and I’m proficient in Python for data extraction, transformation, and orchestration. My work spans containerized data platforms, real-time and batch pipelines, warehouse modeling (star/snowflake schemas), API integrations, and cloud-based analytics solutions. I’ve designed and deployed pipelines that synchronize databases, ingest external APIs (e.g., New York Times, Wikipedia), model complex datasets, and automate production-grade workflows across multiple environments. As a Kaggle Datasets Expert and Python developer with a passion for clean data design, I focus on creating reproducible, high-quality datasets, scalable architectures, and well-tested transformation layers. I enjoy translating business problems into technical solutions—whether designing ERDs, implementing dbt models, optimizing SQL queries, or orchestrating multi-stage workflows in Airflow. I’m also experienced in Power BI for visualization, enabling end-to-end delivery from raw data to insights. My goal is to build robust, maintainable pipelines that empower organizations to make better data-driven decisions.

Data Manager with over 8 years of experience leading data as a strategic business asset. Specialized in e-commerce, I have developed end-to-end solutions for data extraction, integration, and analytics, transforming large volumes of information into high-impact business decisions. With solid expertise in Amazon Vendor Central and Seller Central, I have led automation projects and large-scale catalog monitoring, optimizing sales, inventory, and PPC campaigns. Knowledgeable in Python, SQL, and Google Apps Script, alongside key tools such as BigQuery, Airtable, Power BI, Looker, MySQL, Google Sheets, and Excel. In recent years, I have driven applied AI initiatives, combining best practices in Prompt Engineering with agents developed in Python and no-code platforms, as well as workflow automations using Zapier, Make.com, and bots in Slack and Notion. As a leader, I have built and consolidated data teams from scratch, driving the transition from manual processes to secure, automated infrastructures.

Most data pipelines don’t fail because of code. They fail because they weren't built for scale. With 5+ years of experience engineering data systems at companies like Danone and Zurich, I help businesses transform fragile prototypes into resilient, production-grade infrastructure. I don’t just move data; I build the "Source of Truth" that leadership and AI systems actually trust. ➔ Productionizing AI Pipelines: Hardening Python prototypes into scalable RAG and LLM infrastructures (Azure). ➔ Infrastructure-as-Code: Building automated, modular ETL/ELT pipelines that don't require daily manual fixes. ➔ The "One-Source" Dashboard: Integrating messy data from APIs, SaaS (Shopify, HubSpot), and databases into clean Snowflake/BigQuery layers. ➔ Performance Recovery: Optimizing slow SQL queries and high-cost cloud warehouses to save you thousands in monthly spend. ➔ Technical Writing for Data & AI Teams: Creating product documentation, implementation guides, architecture documentation, data dictionaries, knowledge bases, and thought leadership content that makes complex systems easier to understand and adopt. 🛠 Tech Stack Languages: Python (FastAPI, Pandas, PySpark), SQL Data Engineering: ETL/ELT Pipelines, Data Warehousing, Data Modeling, Data Quality, Data Governance Cloud & Warehousing: Snowflake, BigQuery, Databricks, Azure Data Factory, Azure Data Lake, AWS (S3, Athena, Glue) Orchestration & Transformation: Apache Airflow, dbt Analytics & BI: Tableau, Power BI Development & Collaboration: Git, GitHub, VS Code Data Ops: API Integrations, Data Validation, Workflow Automation Technical Writing: Product Documentation, API Documentation, User Guides, Knowledge Bases, Data Dictionaries, Technical Blog Content ✅ Why Me? 5+ Years Experience: I've seen what breaks at the enterprise level and how to prevent it in your startup. Hands-On Builder & Technical Writer: I can both build the system and explain it clearly to engineers, stakeholders, and customers. Speed over Perfection: I focus on shipping high-impact systems that drive revenue, not just technical documentation. Transparent Communication: You get regular updates and a partner who challenges requirements to find better solutions. Ready to clean up your data debt?

Hello, I'm Vairag Borad, a Microsoft Certified: Fabric Data Engineer and Microsoft Certified Power BI professional with over 6+ years of experience designing modern analytics platforms, data engineering solutions, and business intelligence applications. I specialize in building end-to-end Microsoft Fabric solutions that enable organizations to transform raw data into trusted, scalable, and actionable insights. Whether you need to build a Fabric Lakehouse, implement Medallion Architecture, develop high-performance Spark notebooks, create Power BI semantic models, or migrate existing data platforms to Microsoft Fabric, I'm here to help. 🔹 My Expertise Microsoft Fabric Lakehouse & Medallion Architecture: Design and implement Bronze, Silver, and Gold layers using Delta Lake, ensuring scalable, maintainable, and high-quality data pipelines. Data Engineering & Spark Notebooks: Develop efficient PySpark notebooks for data ingestion, transformation, cleansing, validation, CDC implementation, incremental loading, and optimization. Data Factory Pipelines: Build automated data pipelines for orchestration, scheduling, monitoring, parameterization, and error handling. Data Warehouse: Design dimensional models, implement fact and dimension tables, optimize SQL workloads, and support enterprise reporting. OneLake Integration: Build centralized enterprise data platforms using OneLake for unified data storage and governance. Performance Optimization: Optimize Spark jobs, partitioning strategies, Delta tables, caching, broadcast joins, and pipeline execution for large-scale datasets. Monitoring & Data Quality: Implement logging, auditing, exception handling, and data quality validation throughout the data engineering lifecycle. Power BI Power Query & M: Extract, transform, and prepare data from multiple enterprise data sources. Data Modeling & DAX: Build optimized semantic models, create complex DAX measures, and develop interactive dashboards. Row-Level Security (RLS): Implement secure access controls for enterprise reporting. Power BI Service: Publish, manage, and optimize reports, workspaces, refresh schedules, and deployment pipelines. SQL & Python Advanced SQL: Develop optimized SQL queries, stored procedures, views, and performance tuning for analytics workloads. PySpark & Python: Build scalable data engineering solutions for ETL, automation, data validation, and advanced transformations. 🔹 Why Choose Me? Microsoft Fabric Specialist: Experienced in building modern analytics platforms using Microsoft Fabric's Data Engineering, Lakehouse, Warehouse, Data Factory, and Power BI capabilities. End-to-End Data Engineering: From data ingestion and transformation to semantic modeling and reporting, I deliver complete analytics solutions. Performance-Focused: I build scalable, efficient, and maintainable solutions that handle enterprise-scale data. Business-Oriented: I focus on delivering trusted data products that support informed business decisions. Clear Communication & Reliable Delivery: I provide transparent communication, regular progress updates, and high-quality deliverables on schedule. I'm excited to help organizations modernize their data platform with Microsoft Fabric and unlock the full value of their data. Let's connect to discuss your project and how I can help deliver a scalable, enterprise-grade analytics solution. Best regards, Vairag Borad

✅ 8+ Years as a Data Engineer 📊 Successful Data Engineering Projects Across 22+ Industries in 5 Countries 👨‍💼 Leading a Team of Data Engineers 🌎 Fluent English Hi, I’m Roman — Senior Data Engineer, Data Engineer Consultant, and Enterprise Data Engineer with extensive experience building scalable data platforms, cloud ecosystems, and modern analytics infrastructure. As a Data Engineer, I help companies design, optimize, and modernize enterprise data environments that transform raw information into actionable business intelligence. My background as a Data Engineer covers the full lifecycle of data engineering — including ETL development, cloud migration, data warehouse architecture, real-time processing, and analytics automation. Why Clients Choose Me ⚡ Senior Data Engineer experienced in enterprise-scale ETL and cloud solutions 📈 Data Engineer focused on scalable analytics architecture and performance optimization 🌎 Fluent English communication and stakeholder management 👨‍💼 Lead Data Engineer with experience managing distributed engineering teams 🔍 Business-oriented Data Engineer focused on automation and measurable outcomes Core Expertise Data Engineering & ETL: Azure Data Factory (ADF), SSIS, Apache Spark, Databricks, PySpark, Apache Kafka, dbt Core, Data Pipeline Automation, Data Migration & Transformation, Batch & Real-Time Processing — delivered by an experienced Data Engineer. Data Warehousing & Architecture: Enterprise Data Warehouse (DWH), Lakehouse Architecture, Databricks Lakehouse, OLAP & SSAS, Data Modeling, Data Governance, Azure Synapse Analytics, Snowflake, BigQuery — implemented by a Senior Data Engineer. Databases: Microsoft SQL Server, PostgreSQL, MySQL, Oracle, Azure SQL Database, MongoDB, Neo4j, Redis, SQLite — managed and optimized by a Data Engineer. Cloud Platforms: Microsoft Azure, AWS (Glue, Athena, S3, MSK, EC2, RDS), Snowflake, Office 365 — modern cloud ecosystems built by a Data Engineer. Programming & Analytics: Python, SQL, Power BI, DAX, Power Query, API Integrations, Data Automation — advanced technical expertise from a Data Engineer. 💼 Services I Offer 🛠️ ETL Pipeline Development Data Engineer building scalable ETL/ELT pipelines Data Engineer automating ingestion and transformation workflows Data Engineer optimizing existing processes and infrastructure Data Engineer integrating APIs, SaaS, ERP, and CRM systems 🛠️ Data Warehouse Engineering Data Engineer designing enterprise DWH solutions Data Engineer implementing scalable analytics platforms Data Engineer creating OLAP models and data marts Data Engineer improving governance and data quality frameworks 🛠️ Cloud Data Engineering Data Engineer implementing Azure cloud data platforms Data Engineer leading cloud migration and modernization initiatives Data Engineer designing lakehouse architecture solutions Data Engineer processing big data using Spark and Databricks 🛠️ Data Integration & Automation Data Engineer connecting SQL, APIs, Excel, ERP, and CRM systems Data Engineer automating reporting and workflows Data Engineer configuring orchestration and refresh processes Data Engineer centralizing enterprise analytics ecosystems 🛠️ BI & Analytics Support Data Engineer preparing optimized datasets for reporting Data Engineer improving Power BI data models Data Engineer supporting executive dashboards and KPI tracking Data Engineer increasing reporting scalability and performance As a dedicated Data Engineer, my goal is to help businesses create reliable, scalable, and future-ready data platforms that support analytics, automation, and strategic decision-making. Whether you need a Senior Data Engineer for ETL development, a Cloud Data Engineer for migration projects, or a Lead Data Engineer to architect a complete analytics ecosystem — I can help. 📩 Send me a message and let’s discuss how a Data Engineer can accelerate your business goals.