Sr Data Engineer

Smart Energy Water; Dadri; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Smart Energy Water in India is seeking an experienced Data Engineer with 5–7 years of hands-on ETL/ELT, database engineering, and big data processing to design and maintain reliable data pipelines in production. You will work with PostgreSQL, SQL Server, Python, and REST APIs to build complex data integrations, optimize queries, and ensure data quality across systems.

The role requires strong SQL skills, data modeling expertise, and the ability to troubleshoot end-to-end data issues in a

Qualifications

• 5–7 years of Data Engineering/ETL experience.
• Strong SQL and Python skills.
• Experience with PostgreSQL and SQL Server.
• Experience with complex data integrations and data synchronization.
• Familiarity with REST APIs, SFTP, and file-based integrations.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing.
• Build data integrations using REST APIs, SFTP, files, webhooks, and database interfaces.
• Develop bi-directional data integrations between applications, databases, and external systems.
• Implement data validation, logging, auditing, and monitoring for critical pipelines.

Skills

Data Engineering

ETL/ELT

SQL

Python

PostgreSQL

SQL Server

Data pipelines

REST APIs

Big Data

Data Integration

Education

Bachelor's/Master's degree in Computer Science/IT/Engineering

Tools

Talend

SSIS

MongoDB

Kafka

Git

Azure DevOps

CI/CD

Job description

Role Overview

We are looking for an experienced Data Engineer with 5–7 years of hands-on experience in ETL/ELT, database engineering, Big Data processing, and complex bi-directional data integrations. The candidate should have strong SQL and database expertise, experience working with large datasets, and the ability to design, develop, optimize, and support reliable data pipelines in production environments.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing.
• Build data integrations using REST APIs, SFTP, files, webhooks, and database-to-database interfaces.
• Develop and support bi-directional data integrations between applications, databases, and external enterprise systems.
• Implement data synchronization, incremental processing, reconciliation, error handling, retries, and duplicate/missing-data prevention.
• Develop complex SQL queries, stored procedures, functions, views, and data transformations.
• Work extensively with PostgreSQL and SQL Server; exposure to MongoDB is preferred.
• Perform database and query performance tuning, including execution-plan analysis, indexing, joins, partitioning, locking/blocking, and long-running query optimization.
• Work with large datasets and distributed processing frameworks; optimize data processing for scalability and performance.
• Implement data validation, quality checks, logging, auditing, and monitoring for critical pipelines.
• Troubleshoot production ETL, database, integration, and data-quality issues and perform root-cause analysis.
• Collaborate with application, product, DBA, DevOps, and client teams to resolve end-to-end data issues.

Required Technical Skills

Must Have:

• 5–7 years of Data Engineering / ETL experience
• Strong SQL and Python skills
• Strong hands-on experience with PostgreSQL and SQL Server
• Good understanding of ETL/ELT and data pipeline architecture
• Experience with complex data integrations and data synchronization
• Experience with REST APIs, SFTP, file-based and database integrations
• Strong understanding of database performance tuning and optimization
• Experience handling large-volume datasets
• Good understanding of data modeling, data quality, validation, and reconciliation
• Strong troubleshooting and problem-solving skills

Good to Have:

• Talend / SSIS / other ETL tools
• MongoDB
• Kafka or other streaming technologies
• Git, Azure DevOps/GitHub and CI/CD

Preferred Candidate Profile

The ideal candidate should be comfortable working across the complete data lifecycle:

Candidates who have experience working with multiple databases, high-volume data, complex bi-directional integrations, and performance-critical production workloads will be preferred.

• Strong analytical and problem-solving ability
• Good understanding of data architecture and integration patterns
• Ability to independently troubleshoot complex data issues
• Ownership of deliverables and production issues
• Good communication and cross-functional collaboration skills

Education: Bachelor's/Master's degree in Computer Science, IT, Engineering, or related technical discipline.