Sr. Data Engineer

R Systems; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

R Systems, located in Dadri, Uttar Pradesh, is seeking an experienced Data Engineer with over 8 years of expertise in data architecture and engineering. The successful candidate will demonstrate proficiency in delivering production-grade Lakehouse environments and modern data stack tools, including Databricks and AWS services.

The role requires advanced knowledge of orchestration using Apache Airflow and a strong background in data transformation and modeling techniques, particularly with dbt and PySpark.

Qualifications

• 8+ years of experience in Data Engineering or Architecture.
• Expertise in delivering production-grade Lakehouse environments.
• Extensive experience with modern data stack tools.

Skills

Data Engineering

Databricks

Amazon Redshift

Apache Iceberg

Delta Lake

dbt (Core)

PySpark

Python

DuckDB

Apache Airflow

AWS

Kubernetes

Job description

Qualifications

• 8+ Years in Data Engineering / Architecture: Proven experience delivering production-grade Lakehouse environments for high-concurrency (1,000+ user) organizations.
• Modern Data Stack Fluency: Extensive experience withDatabricks(Lakehouse/Unity Catalog) and high-performance warehouses likeAmazon Redshiftor Snowflake.
• Open-Table Formats: Deep hands-on expertise withApache Icebergor Delta Lake, including optimization strategies for partitioning and schema evolution.
• Transformation & Modeling: Mastery ofdbt (Core)for complex SQL-based modeling andPySparkorPythonfor sophisticated data processing.
• High-Efficiency Compute: Familiarity with vectorized/embedded engines likeDuckDBfor specialized or cost-sensitive processing tasks.
• Orchestration Mastery: Advanced experience withApache Airflow, specifically in designing resilient, dependency-aware DAGs in resource-constrained environments.
• Cloud Ecosystems: Expert-level knowledge of AWS (S3, EC2, IAM) or equivalent services in Azure/GCP, with a focus on storage-compute separation.
• Experience with open-source catalog implementations likeApache Polaris.
• Knowledge ofData Opsprinciples and automated data quality testing frameworks.
• Experience translating technical debt and architectural roadmaps for C-level executives.
• Background in managing fixed-resource infrastructure (e.g., EC2/VM-based processing) vs. elastic serverless models.
• Kubernetes (K8s). Deep understanding of Pods, Deployments, Services, ConfigMaps, and Secrets management.