I will create data pipelines on cloud using spark sql
Transforming data into insights: Driving innovation
Sobre este Serviço
Build reliable, scalable data pipelines that transform your business.
Struggling with data ingestion, transformation, or processing? Want to migrate to Cloud? I create end-to-end pipelines using Apache Spark, Python, and cloud services (AWS/Azure) that automate workflows and deliver production-grade insights.
What I offer:
- ETL & ELT pipelines (batch & real-time streaming)
- Cloud deployment: AWS Glue, Lambda, EMR, Azure Data Factory, Databricks, Snowflake
- Real-time processing: Kafka, Kinesis, Event Hubs
- Data lake architecture: Apache Iceberg, Apache Hudi
- API integration with S3, Aurora PostgreSQL, MySQL , DynamoDB
- Database migration (zero downtime)
- Data quality checks & validation
- Custom monitoring dashboards
- Performance optimization (20%+ improvement)
- BI tool integration (Power BI, Tableau)
Why choose me:
- AWS & Databricks Certified
- 5+ years production experience
- Millions of records processed daily
- Enterprise client experience
- Fast communication & clean code
- 30-day post-delivery support
Tech: Python, SQL, Spark, Kafka, AWS, Azure, Databricks, Snowflake, PostgreSQL, MySQL
Message before ordering for perfect project scoping!
Meu portfólio
Outros serviços de Engenharia de Dados que eu ofereço
Perguntas frequentes
Do you work with sensitive data?
Yes! I sign NDAs and follow GDPR/CCPA guidelines. No data is stored locally—100% cloud execution.
What if my pipeline breaks after delivery?
I offer 7 days of free support to fix issues. For peace of mind, add extended monitoring (+$100) with CloudWatch alerts.
How do you handle small vs large workloads?
Precision is key! Small: Serverless Lambda (fast, cheap). Large: Glue (cost-optimized DPUs, partitioning). Proven: Split workloads saved a client 55% vs one-size-fits-all solutions.
What if I’m unhappy with the results?
I prioritize your satisfaction: 🛠️ 2 free revisions (Standard/Premium packages). 💸 100% refund if I fail to meet agreed specs.
