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!

If your data team spends more time fixing pipelines than reading insights, that's not a people problem — it's an infrastructure problem. I'm a Top Rated Analytics Engineer with 6+ years building data infrastructure that operations teams actually rely on. I've worked across fintech (Zeta), agri-tech (Nurture.Farm / UPL), and growth-stage startups — designing warehouse architectures, building dbt pipelines, and creating dashboards that drive real decisions. Two results that tell you what I actually do: ⦁ Reduced a critical Redshift model runtime from 8 minutes to 40 seconds by redesigning sort keys, unique keys, and materialization strategy — unblocking daily reporting for an entire product team. ⦁ Cut machine breakdown response time from 48 hours to 24 hours for 93% of a 500+ machine fleet through real-time alerting dashboards connected to live operational data. What I build for clients: ⦁ Cloud data warehouses on Redshift and BigQuery — structured in dbt with full lineage, tests, and documentation ⦁ Airflow-orchestrated pipelines that run on schedule and alert you when they don't ⦁ Tableau, Power BI, Looker Studio, and Superset dashboards built around the decision, not the data ⦁ Data quality frameworks with row-level validation and automated monitoring ⦁ Real-time analytics pipelines using AWS Athena, Python automation, and SQL I work best with founders, data leads, and product teams who want analytics to be a competitive advantage, not a maintenance burden. I document everything, communicate proactively, and deliver what I said I would — when I said I would. If you have a data pipeline, warehouse, or dashboard problem — send me a message. I'll tell you within 24 hours whether I can fix it and exactly how.

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 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 businesses turn scattered data into clear, decision-ready intelligence. With 10+ years in Business Intelligence and customer analytics, I specialize in building structured, scalable BI systems that go beyond reporting — enabling leadership to understand what’s driving revenue, retention, and performance. I work across customer and marketing analytics, focusing on: • Revenue and profitability visibility • Customer lifecycle analytics (acquisition, retention, churn) • Marketing performance and campaign effectiveness • Sales and product performance dashboards • Executive-level reporting with strong data governance I’ve led enterprise BI initiatives across Hospitality, Automobile, Manufacturing, Infrastructure, and Retail domains — transforming analytics from static reports into strategic decision-support systems. My approach is structured and business-focused: • Clean data modeling and governance first • Clear KPI definitions aligned to business goals • Intuitive dashboards built for adoption • Performance-optimized and scalable architecture • Scenario simulators and what-if tools for planning If you're looking for someone who understands both data architecture and business decision-making — not just visuals — I’d be glad to discuss your goals.