Lead Data Engineer - O&G

USEReady Inc.; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

USEReady Inc. seeks a hands-on Lead Data Engineer (8–12 years) to design, build and optimize scalable data pipelines and cloud data platforms.

The role focuses on Operations, Engineering and Finance data with SCADA, PI systems, historians, telemetry, IoT, and OT/IT integration across Microsoft Fabric, Azure data services, Databricks and Snowflake. You will own data acquisition, integration, and governance, lead Bronze-Silver-Gold data layers, develop batch and streaming pipelines, ensure

Qualifications

• Experience: 8–12 years in software or data engineering with cloud-native data platforms.
• Domain focus: operations, engineering, and finance data.
• Industrial OT systems: SCADA, PI, historians, telemetry, IoT and OT/IT integration.
• Core tech stack: Microsoft Fabric, Azure data services, Databricks and Snowflake.
• Engineering tools: SQL, Python, Spark, Airflow and CI/CD frameworks.
• Operational mindset: scale real-time/batch pipelines with RTO/RPO, quality and observability.

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 OT and IT environments for seamless analytics platform integration.
• Cross-Functional Data Architecture: Architect pipelines across Operations, Engineering and Finance.
• Pipeline Development: Design batch and near-real-time ingestion using ETL/ELT, CDC, APIs, and events.
• Medallion Architecture: Lead Bronze, Silver, Gold layers with quality controls and lifecycle management.
• Data Access & Integration: Build data access services and APIs for downstream analytics and AI workloads.
• Data Governance & Security: Implement RBAC, masking, encryption, lineage, and metadata tracking.
• DataOps & Reliability: Maintain pipelines with monitoring, testing, reconciliation, and incident response.
• Performance & FinOps: Optimize cloud resources, queries, and storage on Azure, Databricks, Snowflake.

Skills

Operational mindset

Cross-domain data work

Industrial OT data knowledge

Data governance

Tools

Microsoft Fabric

Azure data services

Databricks

Snowflake

SQL

Python

Spark

Airflow

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.