Lead Data Engineer - OandG

USEReady; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

USEReady is seeking a hands-on, technical Lead Data Engineer (8–12 years) to design, build, and optimize scalable data pipelines and modern cloud data platforms in Bengaluru. You will work across Operations, Engineering, and Finance data, integrating SCADA, PI systems, historians, telemetry, IoT, and OT/IT source systems with Microsoft Fabric, Azure data services, Databricks, and Snowflake.

The role emphasizes data architecture, batch and near-real-time ingestion, data quality, security, and

Qualifications

• 8–12 years of professional software or data engineering experience with a strong focus on cloud-native data platforms.
• Seasoned experience working directly with Operations, Engineering, and Finance data.
• Hands-on experience with SCADA, PI systems, industrial historians, telemetry, IoT, and OT/IT source system integration.
• Hands-on proficiency with Microsoft Fabric, Azure data services, Databricks, and Snowflake.
• Advanced fluency in SQL, Python, Spark, Airflow and modern orchestration/CI/CD frameworks.

Responsibilities

• Own data acquisition, contextualization, integration, and scalability across historian, telemetry, SCADA, IoT, and future operational data platforms.
• Bridge OT and IT environments, ensuring seamless integration between industrial source systems and enterprise analytical platforms.
• Architect and build pipelines handling complex datasets spanning Operations, Engineering, and Finance domains.
• Design and build batch and near-real-time ingestion pipelines utilizing ETL/ELT, CDC, APIs, and event-driven integration.
• Lead Bronze/Silver/Gold data layers with transformation boundaries and data quality controls.
• Build and maintain enterprise data access services, APIs, and governed sharing patterns.
• Embed security, data masking, encryption, RBAC, lineage, and metadata tracking into data workflows.
• Maintain production data pipelines with monitoring, observability, automated testing, and incident response.
• Optimize cloud resource consumption, query performance, and storage costs across Azure, Databricks, and Snowflake.
• Uphold engineering best practices including source control, reviews, IaC, and automated deployments.

Skills

Operational data integration

Cross-functional collaboration

Data governance

DataOps

ETL/ELT design

Tools

SQL

Python

Spark

Airflow

CI/CD tooling

Job description

Job Description:

Position Summary

USEReady is seeking a hands-on, technical Lead Data Engineer (8–12 years experience) to design, build, and optimize scalable data pipelines and modern cloud data platforms. The ideal candidates are seasoned professionals with deep experience working across Operations, Engineering, and Finance data, bringing specialized knowledge of SCADA, PI systems, historians, telemetry, IoT, and OT/IT source system integration. This role will focus heavily on execution across Microsoft Fabric, Azure data services, Databricks, and Snowflake.

Key Responsibilities

• Operational & Industrial Data Integration: Own data acquisition, contextualization, integration, and scalability across historian, telemetry, SCADA, IoT, and future operational data platforms.




• OT/IT Source System Integration: Bridge operational technology (OT) and information technology (IT) environments, ensuring seamless integration between industrial source systems and enterprise analytical platforms.




• Cross-Functional Data Architecture: Architect and build pipelines handling complex datasets spanning Operations, Engineering, and Finance domains.




• Pipeline Development: Design and build batch and near-real-time ingestion pipelines utilizing ETL/ELT, change data capture (CDC), APIs, and event-driven integration.




• Medallion Architecture: Lead the hands-on delivery of Bronze, Silver, and Gold data layers with clear transformation boundaries, data quality controls, and lifecycle management.




• Data Access & Integration: Build and maintain enterprise data access services, APIs, and governed sharing patterns to support downstream analytics, applications, and AI workloads.




• Data Governance & Security: Embed security, data masking, encryption, role-based access controls (RBAC), lineage, and metadata tracking directly into data workflows.

• DataOps & Reliability: Maintain production data pipelines with active monitoring, alerting, observability, automated testing, data reconciliation, and incident response.




• Performance & FinOps: Optimize cloud resource consumption, query performance, and storage costs across Azure, Databricks, and Snowflake environments.




• CI/CD & Engineering Standards: Uphold engineering best practices including source control, peer reviews, infrastructure-as-code, and automated deployment pipelines.

Required Qualifications

• Experience: 8–12 years of professional software or data engineering experience with a strong focus on cloud-native data platforms.




• Domain & Functional Data: Seasoned experience working directly with Operations, Engineering, and Finance data.




• Industrial & OT Systems: Hands-on experience with SCADA, PI systems, industrial historians, telemetry, IoT, and OT/IT source system integration.




• Core Tech Stack: Hands-on proficiency with Microsoft Fabric, Azure data services, Databricks, and Snowflake.




• Engineering Tools: Advanced fluency in SQL, Python, Spark, Airflow and modern orchestration or CI/CD frameworks.




• Operational Mindset: Demonstrated experience scaling real-time/batch pipelines while maintaining strict RTO/RPO, data quality, and observability standards.