Role & responsibilities

- Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Delta Lake
- Build real-time and batch data ingestion pipelines from diverse operational systems using high-performance Kafka data pipelines.
- Implement data transformations that serve digital twin platforms and operational analytics
- 2+years of Technical Leader ship Experience
- Integrate Kafka event streams with Databricks for real-time operational state updates
- Implement data quality checks using Delta Live Tables expectations
- Ensure data governance compliance through Unity Catalog (lineage, access control, metadata)
- Optimize pipeline performance, reliability, and cost efficiency
- Write clean, well-documented, and testable code following engineering best practices
- Collaborate with ML engineers to deliver feature-engineered datasets
- Participate in code reviews, knowledge sharing, and continuous improvement initiatives
- Support production data systems through monitoring, troubleshooting, and incident resolution.
- Build business data warehouse solutions using Terradata for business intelligence.

Preferred candidate profile

Our core data platform stack includes:

Data Platform & Lakehouse

- Databricks as the single point of truth for all data




- Realtime Data Pipelines implemented using Kafka for data ingestion.
- Databricks SQL for analytical queries
- Unity Catalog for metadata management and governance
- Terradata for data warehouse and business intelligence.

Stream & Event Processing

- Apache Kafka for real-time event ingestion
- Structured Streaming for continuous data processing
- Delta Live Tables for declarative, quality-enforced pipelines

Data Quality

- Delta Live Tables expectations for data validation
- Data profiling and anomaly detection

Preferred Qualifications

- 7+ years of hands-on data engineering experience
- Track record of building and maintaining production-grade data pipelines
- Experience with Delta Live Tables for declarative pipeline development
- Experience working in agile, cross-functional teams
- Familiarity with time-series data patterns and operational data modelling

Highly Desirable

- Experience building data pipelines for digital twin or simulation platforms
- Familiarity with operational state modeling for real-time systems
- Exposure to physics-informed or time-series ML feature engineering
- Experience working with distributed, multidisciplinary teams
- Exposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus

📌 Lead Data Engineer (Hyderabad)
🏢 Talentrabbit
📍 Hyderabad