Hire the Best HBase Specialists in Bengaluru, IN

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. 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, AWS Step Functions, 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 governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, 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 | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ 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 am a passionate full stack hands-on Software Architect with more than 19 years of experience in architecting, designing and developing solutions using apt technology stack. I am experienced in .NET / C#, Java, J2EE, Spring / Springboot, REST API, React, Angular, Javascript, HTML, CSS, ASP.NET, C++, Python, Oracle, PostgreSQL, MS SQL Server, Amazon Web Services. My healthcare domain expertise includes IHE Radiology workflow, DICOM, HL7 2.3, DVTk, JDICOM, Orion Rhapsody, Mirth, DCMTk, Wireshark. User-focused, system-level thinking approach, keen attention to security, design patterns with clean and maintainable code are my greatest skills. I am practicing agile software development for more than 10 years with Certified Scrum Master certification from Scrum Alliance with proven track record of improving team productivity and performance. Having worked with multi-cultural customers and teams, both onsite as well as fully remote, I am a self-motivated and proactive engineer who loves to step up to new challenges. Looking forward to working with you!

I help brands build and automate their SAP, Veeva, Labware BI reporting and data pipelines—saving $300K+/year by delivering real-time insights via SQL, Python, Power BI/Tableau & Databricks. • Quality systems Dataset Expertise: SAP ECC technical data (QM, MM), Veeva Quality, Labware • Data Engineering & ETL: Python, PySpark, Databricks, dbt, Fivetran, • Cloud Data Warehousing: Snowflake, SQL Server, Google Cloud Functions • BI & Visualization: Power BI, Tableau, Looker (LookML), Advanced Excel (XLOOKUP, Power Query) • Data Automation & Alerts: Automated email delivery, scheduled Python jobs, Slack/SMS webhooks, make.com • Stakeholder Management: Engaging SVPs to roll out analytics to 300+ users globally Some accomplishments 1. Led an automated email feature (Python + Databricks) to deliver performance scores to 750+ Estée Lauder suppliers—saving $25K in manual distribution costs. 2. Built a Databricks ETL pipeline for Veeva Quality data (Python, PySpark, dbt), slashed data prep time by 80%, and realized $20K in annual savings. 3. Optimized SAP SQL queries to generate ad-hoc supply-chain reports (10M+ rows), enabling 300+ users to access real-time insights—prevented $200K in lost revenue by accelerating product releases. If you need a turnkey BI reporting, data-automation or ETL solution—whether building interactive dashboards, automating daily data alerts —invite me to your project. I’ll deliver a tailored proposal within 24 hours.

If you have projects in Apache Superset and require help on the following, please get in touch: - Superset infrastructure, administration and deployment. - Superset dashboard development and best practices. - Superset customisations - Business Intelligence roadmaps and expansion. I have been in the Business Intelligence, Data Management and Digital Transformation space for 8+ years. A few names I have helped in their journey of analytics and BI, Worldbank, Vodafone, Tatasteel, Sentosa, IBM and several startups. Tools are only one part of the story. Being able to use the tools to create a great experience is something else altogether. I am particularly good at unearthing trends and patters in data mountains. This "data mountain" could be the www or your database(s).

👋 I help companies with Data Analytics, Business Intelligence, and KPI reporting turn messy data into clear, reliable decisions. • Lead Analytics Architect with 10+ years of experience • Built enterprise-grade analytics at Hinge Health, Innovaccer, Airbnb, and Ola • Specialized in measurement systems, dbt-based data models, and AI agents that reduce decision delays for leadership teams 🧠 How I help Most teams don’t struggle because they lack dashboards. They struggle because their data can’t explain why something changed. I design the system behind the answers, not just the reports. • 📐 Metric & Measurement Architecture – Map business KPIs to operational drivers – Replace vanity metrics and dashboards with decision-ready insights • 🧱 dbt-Based Single Source of Truth – Build clean, test-validated data models (dbt, SQL) – Power BI dashboards and executive reporting • 🤖 AI Agents for Proactive Insights – Build AI-driven analytics automation (Python, LangGraph) – Surface root-cause analysis and anomaly detection in Slack or Teams 📊 Selected work & outcomes • Centralized measurement system (HealthTech) Led a full dbt migration to standardize metric definitions across teams, enabling test-validated models used by multiple downstream data products and supporting IPO readiness. • AI-driven metric monitoring (Leadership KPIs) Built an internal analytics agent to monitor weekly KPIs and surface root-cause insights, enabling proactive leadership interventions and reducing manual analysis. • Revenue-impacting analytics products Owned the end-to-end analytics product lifecycle at a healthcare data platform, contributing to $6M ARR growth through improved product insights and usability. • Operational forecasting & cost optimization Designed forecasting and KPI monitoring tools that reduced support response times and delivered $1M+ in cost savings across operations teams. 👉 All examples reflect production systems used by real teams. 🔍 Typical problems I help with • Leadership doesn’t trust numbers across teams • Metrics change depending on who built the report • Analysts spend time answering repetitive ad-hoc questions • Data foundations are not ready for AI or automation ✅ Why teams choose me • Enterprise-grade experience (HIPAA, FinTech, HealthTech, IPO readiness) • Strong business + technical depth — I translate executive questions into scalable systems • Proven impact: $5M+ annual savings, $6M ARR growth, $1B+ IPO readiness • Built for AI-first analytics, not retrofitted later 🧩 What you can hire me for • Data Analytics & Business Intelligence projects • Dashboard development for executives and leadership teams • KPI design, metric definition, and reporting • dbt data modeling, testing, and documentation • Forecasting, anomaly detection, and root-cause analysis • AI-driven analytics automation and alerting 👉 Clear scope. Production-focused. No generic consulting. 🤝 What working with me looks like • Clear problem framing before writing code • Frequent check-ins with business stakeholders • Clean handover with documentation and ownership 🛠️ How engagements typically start • Short discovery call to frame the problem • Clear scope with deliverables and timeline • Build, validate, and iterate with stakeholders 👉 No open-ended work. No surprise scope. ⏳ Current engagement note • Taking on a limited number of early Upwork engagements to establish long-term partnerships • Projects are scoped carefully to prioritize fit, trust, and strong outcomes • Rates will evolve to reflect the full strategic scope of this work 📩 If you want faster answers without more dashboards, let’s talk. Message me with your current analytics bottleneck, and I’ll help you map a clear path forward.

Microsoft Certified Fabric Analytics Engineer Associate (DP-600) | Power BI & Microsoft Fabric Developer I turn operational and financial data into reliable analytics solutions that leaders can act on. I build Power BI semantic models, dashboards, and reports using DAX, Power Query, and star-schema modeling, alongside hands-on Microsoft Fabric solutions across Lakehouse, Warehouse, Data Pipelines, Notebooks, and Direct Lake. I also work with Fabric IQ, Ontology, security, governance, and deployment to deliver scalable, end-to-end analytics solutions. 🎯 My focus: clean data models, reliable KPIs, and dashboards people actually open. 🛠️ What I build (end to end): ✅ Power BI dashboards - executive P&L, operations, safety (HSEQ) and project (PMO) reporting with DAX, Power Query, star-schema models and row-level security. ✅ Microsoft Fabric (hands-on) - end-to-end on OneLake: Lakehouse + Warehouse medallion (Bronze->Silver->Gold), Fabric Notebooks (Python), Dataflows Gen2, T-SQL stored procedures, and Fabric Data Pipelines feeding Power BI semantic models. ✅ Data engineering - ETL/ELT into a Fabric Lakehouse/Warehouse; OneLake shortcuts; pulling data from source systems (e.g. Procore) into Fabric. ✅ Data quality - built-in exception / DQ reporting so the numbers stay trustworthy. 🧱 Microsoft Fabric stack I work across: OneLake - Lakehouse - Warehouse - Dataflows Gen2 - Fabric Notebooks (Python) - Fabric Data Pipelines - semantic models - Direct Lake. 📊 Where I focus: ✅ Finance / P&L, operations and project (PMO) reporting - the work I do most. 📌 Recent work: ✅ Enterprise energy P&L & operations dashboard - Actual vs Budget, state/site drill-through, DQ exception reporting. ✅ HSEQ dashboard - incidents, near-misses, inspections and registers (Procore data). ✅ PMO / project-health dashboard - project status, budget, schedule and resource utilization. ✅ Procore -> Microsoft Fabric data pipeline (pulling Procore data from the backend into Fabric). 💡 How I add value: ✅ I own the whole flow - pipeline to dashboard - so the numbers stay reliable. ✅ I automated daily reporting of manpower data with Python from different and scattered sharepoint excel files- cutting the time of reporting from 4 hours to 20 minutes. ✅ Clean, structured, well-documented development. 🤝 Why clients work with me: ✅ Power BI depth (DAX, Power Query, RLS) ✅ Hands-on Microsoft Fabric (Lakehouse, notebooks, T-SQL, pipelines) ✅ Data-engineering + data-quality mindset 📩 If you need Power BI dashboards on a solid Microsoft Fabric foundation - from pipeline to report - send me a message and let's turn your data into clarity.