Your role at Dynatrace

We are seeking an experienced Data Engineer to design, build, and optimize scalable data ingestion pipelines for product telemetry and enterprise business applications data. This role operates in a quick‑paced environment, rapidly prototyping data pipelines to enable data exploration, analytics, and downstream consumption.

Responsibilities
- Design and implement modern data ingestion pipelines for business systems data using Fivetran, Python and Bulk APIs, S3-based lakehouse architectures, and streaming ingestion (Kafka, Spark)
- Build end-to-end automated pipelines from source systems to Snowflake, ensuring reliability, scalability, and observability
- Apply advanced SQL in Snowflake for transformation, standardization, and preparation of analytics-ready datasets
- Optimize ingestion performance for large-scale, high-volume datasets using API rate-limit handling, micro-batching, and incremental loading / CDC
- Implement DevOps and CI/CD practices for data pipelines, including version control and deployment automation
- Partner with analysts, SMEs,



and platform teams to rapidly prototype pipelines supporting exploration and evolving requirements
- Monitor, troubleshoot, and optimize ingestion jobs to ensure data freshness, accuracy, and performance

What will help you succeed
- 6+ years of hands-on experience in data engineering and ingestion automation in cloud or hybrid environments
- Proven experience ingesting business application data (CRM, ERP, financial, consumption, renewals systems)
- Advanced proficiency with Python and Fivetran (or similar ETL/ELT tool) for pipelines, automation, orchestration, and validation
- Expertise with Kafka, Spark, and S3 / lakehouse-style storage architectures
- Strong proficiency with Snowflake, ingestion, transformation, and performance optimization
- Deep understanding of ingestion optimization, rate limits, micro-batching, incremental loads, and CDC
- Experience applying DevOps / CI/CD practices to dat

📌 Sr Data Engineer (India)
🏢 Dynatrace
📍 India