Hire the Best Data Warehousing Specialists

Most e-commerce brands and agencies don't have a data problem. They have a trust problem. Tracking breaks. Numbers in GA4, Meta, Google Ads, and Shopify never match. Dashboards get rebuilt by hand every month, and no one's sure which figure to spend against. I fix the whole chain, end to end: from the tag firing on your site, to the BigQuery pipeline that cleans and unifies the data, to the dashboard your team makes decisions on. I'm an Analytics Engineer who builds the data engineering layer (automated pipelines, BigQuery modeling, BI) on top of deep, hands-on tracking implementation roots. That combination is the point. Because I own both the server-side tracking and the pipelines it feeds, the data stays coherent the whole way down, with no hand-offs between three specialists who each blame the other when the numbers don't add up. I work almost exclusively with e-commerce brands and marketing, growth, and advertising agencies (white-label welcome). I speak ROAS, MER, CAC, and LTV, so you tell me the business goal, not the technical spec. --- What I build Marketing & e-commerce data pipelines (GCP / BigQuery), the core of what I do: - Automated ETL/ELT from GA4, Shopify, ad platforms (Meta, Google, TikTok), and CRM into BigQuery - Ingestion via Python, dbt, Fivetran, Stitch, or the GA4 native BigQuery export - BigQuery data modeling: staging, intermediate, and mart layers, partitioning, clustering, incremental models - Data cleaning, normalization, deduplication, and identity stitching across sources - Orchestration and scheduling on GCP: Cloud Run, Cloud Functions, Pub/Sub, Cloud Scheduler - Cost optimization, query tuning and table design so the warehouse scales without surprising your bill - Deliverables: automated pipeline, single source of truth in BigQuery, attribution-ready datasets, documented and modeled tables refreshed on schedule, a warehouse your next analyst can actually read Tracking & analytics implementation, the foundation the data depends on: - GA4: advanced e-commerce, custom events, funnels, attribution-ready data layer - Google Tag Manager, client-side and server-side (Stape or GCP) - Conversion APIs: Meta CAPI, TikTok Events API, Google Ads enhanced conversions, Snapchat, LinkedIn - Client-to-server migration to recover conversions lost to iOS, ITP, and ad blockers - Consent Mode v2 and CMP setup (OneTrust, Usercentrics), first-party capture, hashing, deduplication - dataLayer, JavaScript, and DOM work for custom event tracking - Deliverables: documented tracking plan, validated event and conversion setup, tag and trigger audit, numbers that reconcile across platforms BI & reporting, the part your team actually looks at: - Looker Studio dashboards powered by BigQuery (Power BI / Tableau / Metabase on request) - Revenue analytics, channel performance, funnels, ROAS/CAC/LTV scorecards - Automated SQL transformations and scheduled workflows, no manual monthly rebuilds - Deliverables: CEO-ready dashboard, automated refresh, documentation your team can follow --- Why clients hire me: I combine data engineering, analytics implementation, and BI automation into one workflow. Instead of isolated dashboards or pipelines built on shaky tracking, you get a full-stack, maintainable, accurate data system, with one person accountable from the tag on your site to the number on the dashboard. Agencies can put me behind their own client work: on calls if you want me there, invisible if you don't. Certifications: - Google Cloud Professional Data Engineer (2025) - Google Analytics Individual Qualification (verified by Upwork) - Meta Certified Marketing Developer (Credly) Whether you need a GA4-to-BigQuery pipeline, broken tracking fixed, Shopify analytics modeling, or a complete analytics foundation, tell me what you're trying to decide with the data, and I'll build the system that gets you there.

I'm a results-driven Senior Data Engineer specializing in building cloud-native data pipelines and architectures that transform raw data into actionable business insights. With 100% job satisfaction and a 5-star rating, I deliver solutions that exceed expectations. What I Bring: Cloud Expertise: Azure, GCP, and AWS with deep experience in Databricks, BigQuery, and Data Factory Real-Time Processing: Built streaming pipelines reducing reporting latency from hours to minutes Enterprise Scale: Consolidated 50+ data sources, processed 100M+ daily transactions, and supported 1000+ users Architecture Design: Expert in Lakehouse, Medallion, and Star Schema implementations with strong data governance Proven Results: Reduced reporting latency by 98% through real-time pipeline optimization Improved query performance by 40% with strategic data modeling Achieved 35% increase in compliance reporting accuracy Delivered zero-downtime deployments with automated CI/CD I partner closely with stakeholders to understand business needs and deliver data solutions that drive decision-making. Whether it's building real-time analytics platforms, implementing data governance, or optimizing existing pipelines, I focus on scalable, maintainable solutions. Let's discuss how I can help transform your data into a strategic asset.

I am one of the Top Rated Data Engineer specialists on Upwork. My sophisticated hand-crafted Dataware house/Report/Dashboard design will save your organization significant time, money, and performance. My area of expertise, ✅ Data Modeling (Relational & Dimensional) ✅ Database & DWH Architecture, Design & Development ✅ ETL Architecture, Design & Development (SSIS) ✅ Multidimensional cube Architecture, Design & Development (SSAS) ✅ Printed Report using SQL Server Reporting Services (SSRS) ✅ Power Platform (Power Pivot, Power BI, Power Apps, Power Automate) ✅ MS Azure (SQL DB, Data Factory, Data Lake) I am a serious professional with over 12+ years of experience as a programmer and database specialist. My emphasis has been on creating elegant Normalized/De Normalized database design integrated with user-friendly front-end software (desktop and web applications). I specialize in Business Intelligence and Analytics. It means I have an expert level in creating custom reports from Sales, Purchasing, Inventory, Banking to Financial using any BI Tool and with any Data Sources supported by (Power BI, SSRS, Tableau, Crystal Reports) I also create reports for other External ERP system like(Sage, Misys, Ramco ERP, SalesForce, Quick Book) In my case, I fully understand 100% any database structure(tables and fields) and other technical aspects such as UDT and UDF, validation triggers, simple to complex stored procedures, views, and T-SQL and ETL(SSIS) A detailed-oriented person who loves what I do, can deliver, a fast worker, and able to multitask awaits your invite. INVITE ME TO YOUR JOB!!! less than 5 hrs response time Do Read my Feedback Rite Below.

A Senior Data Engineer with 8+ years of experience building reliable, scalable data pipelines and infrastructure, from data ingestion and transformation through warehousing, streaming, and data analytics with dbt, Snowflake, Airflow across AWS, Azure, and GCP with robust ETL and ELT. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

I help businesses build reliable data pipelines, cloud infrastructure, and backend systems that scale. My core work includes Azure Data Factory pipelines, SQL data warehousing, Snowflakes, Terraform-based infrastructure, AWS/Azure deployments, and backend integrations for data-heavy applications. I focus on production-ready systems that are stable, observable, and built for real business use. I have worked on projects such as: • Building Azure-based ETL pipelines and warehouse processes integrating platforms like Shopify, NetSuite, UKG, Air1, and custom systems • Processing large daily data volumes with incremental and full-sync strategies • Designing SQL procedures, reconciliation workflows, and reporting pipelines for operational and executive dashboards • Automating cloud infrastructure and deployments using Terraform, AWS, Jenkins, Docker, and Kubernetes • Improving performance, reliability, and cost-efficiency in backend and AI-driven systems What I can help with: • ETL / ELT pipelines • Azure Data Factory workflows • Azure SQL / PostgreSQL / SQL optimization • Data warehouse design • Backend API integrations • Terraform infrastructure automation • AWS / Azure deployment workflows • Monitoring, logging, and production reliability improvements Why clients work with me: • I understand both data and backend systems, so I can solve integration problems end-to-end • I care about business outcomes, not just writing code • I communicate clearly and keep delivery practical • I build with maintainability and production use in mind If you need help with a data pipeline, warehouse workflow, backend integration, or cloud infrastructure setup, I’d be glad to discuss your project. Certifications: AWS Certified Solutions Architect HashiCorp Terraform Associate

I build the data infrastructure behind confident business decisions. Clean pipelines, structured warehouses, automated workflows, and dashboards that actually mean something. I am a Data Engineer and BI Developer specializing in end-to-end data solutions across the Microsoft ecosystem. I design and deliver scalable data pipelines, cloud-based warehouses, and analytics-ready environments using Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, SSIS, Python, and SQL, paired with executive-grade Power BI dashboards that turn raw data into real business visibility. My work sits at the intersection of data engineering and business intelligence. I don't just move data. I architect structured, maintainable environments that organizations can own, scale, and trust for long-term decision-making. What I Deliver - End-to-end data pipeline design and implementation using Azure Data Factory, Microsoft Fabric, and Databricks - Data warehouse architecture with clean, well-modeled schemas (star schema, dimensional modeling) built for performance and clarity - ETL/ELT development and automation including ingestion, transformation, scheduling, monitoring, and error handling across multiple source systems - Integration of diverse data sources including CRMs, ERPs, accounting platforms (QuickBooks, Xero), ecommerce systems (Shopify, Amazon), marketing APIs, CSV/Excel files, and cloud databases - Microsoft Fabric implementation including lakehouses, warehouses, pipelines, and paginated reports within the Fabric ecosystem - SQL development, query optimization, and stored procedure design for high-performance reporting - Python scripting for data automation, transformation, and API-based data extraction SSIS package development and maintenance for legacy and hybrid environments - Interactive Power BI dashboards and reports including KPI tracking, contribution margin analysis, profitability reporting, inventory analytics, and operational visibility - Documentation, SOPs, and structured handover materials so internal teams can confidently maintain and extend solutions independently Tools & Technologies - Microsoft Fabric - Azure Data Factory - Azure Synapse Analytics - Azure Data Lake Storage - Databricks - Python - SQL Server & SQL - SSIS - Power BI (Desktop, Service, Embedded, Paginated Reports) - Power Query & DAX - Microsoft Excel How I Work - Full ownership of delivery, from understanding your data landscape through to pipeline implementation, dashboard development, documentation, and team training - Focus on building solutions that are simple, well-structured, and designed for in-house sustainability, not black boxes that create dependency - Whether you need a greenfield data platform, an existing infrastructure restructured, or a reliable reporting layer connected to your operational systems, I bring the engineering discipline and BI expertise to deliver it cleanly and on time If you need a data engineer who can own the full journey from raw data to reliable reporting, let's connect. I'd love to understand your data challenges and build something that actually works.