Role Purpose

This role is responsible for driving enterprise-wide data engineering strategy. It ensures the design, implementation, and continuous improvement of data pipelines, scalable and reusable frameworks, and implement data governance and data quality engines. The position enables trusted, governed data across systems, supporting analytics, compliance, and business operations at ELGi.

Key Responsibilities

Data Engineering & Architecture

- Design scalable, production-grade ETL/ELT pipelines across Azure, AWS, and GCP.
- Develop modular, reusable data engineering frameworks for ingestion, transformation, and orchestration.
- Build Spark, SQL, and Python workflows in Databricks.
- Implement batch, micro-batch, and streaming ingestion patterns.
- Optimize compute, storage, and pipeline performance for cost efficiency.

Data Quality, Governance & Security

- Build custom data quality (DQ) frameworks with rule-based validation.
- Develop DQ dashboards to track coverage and SLA adherence.
- Implement governance standards including metadata, lineage, and RBAC.
- Apply row/column-level security and data masking policies.
- Ensure compliance with GDPR, SOC2, ISO, and internal controls.
- Manage secure secrets using Azure Key Vault / AWS Secrets Manager.

Pipeline Reliability & DevOps

- Set up monitoring, logging, and alerting frameworks for pipeline health.




- Drive test-driven data engineering (unit, integration, regression tests).
- Use Azure DevOps and GitHub for CI/CD automation and version control.
- Improve pipeline stability and reduce failure rates.

Cross-Functional Collaboration

- Collaborate with Data Engineering, Data Architects, Analytics teams, and vendors.
- Partner with ERP, SCM, Logistics, CRM, IoT, and Quality business teams.
- Translate business needs into scalable engineering solutions.

Leadership & Technical Guidance

- Mentor engineers and enforce engineering best practices.
- Guide architectural decisions for data platform modernization.
- Drive innovation in ingestion, transformation, governance, and cloud engineering.

Required Skills and Experience

- 8+ years of experience in data engineering.
- Hands-on expertise with Databricks.
- Solid programming skills in Python and SQL.
- Multi-cloud experience: Azure, AWS, and/or GCP.
- Experience with Azure Data Factory for orchestration.
- Building reusable ETL/ELT frameworks.
- Custom DQ frameworks and DQ dashboard implementation.
- Strong knowledge of governance, metadata, lineage, and security controls.
- Experience with Azure DevOps and GitHub for CI/CD.
- Exposure to ERP, SCM, Logistics, CRM, IoT, and Quality systems

📌 Senior Data Engineer (India)
🏢 ELGI EQUIPMENTS
📍 India