Data Engineer

Role : Data Engineer

Location : Noida, India

Who We Are :

SEW, with its innovative and industry-leading #1 Vertical AI Native Platform, delivers the best Digital Customer Experiences (CX) and Workforce Experiences (WX), powered by AI, ML, and IoT Analytics to the global energy, water, and gas providers. At SEW, the vision is to Engage, Empower, and Educate billions of people to save energy and water. We partner with businesses to deliver platforms that are easy-to-use, integrate seamlessly, and help build a strong technology foundation that allows them to become future-ready.

A Couple of Pointers :

- We are the fastest growing company with over 470+ clients and 1750+ employees.

- Our clientele is based out in the USA, LATAM, Europe, Africa, Canada, Australia, Asia Pacific, MEA.

- Our platforms empower billions of global users.

- We have been awarded 150+ accolades to date. Our clients are continually awarded by industry analysts for implementing our award-winning product.

- We have been featured by Forbes, Wall Street Journal, LA Times for our continuous innovation and excellence in the industry.

Job Description :

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.

Who are we looking for :

SEW Testing team leverages manual & automatic testing to ensure a great product quality during product development and implementation. SEW Testing team is most important arm in company to ensure we identify all the defects and issues before our products being used by end users.

We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our high-quality culture. This person will work closely with product engineers, business analysts, and delivery team to provide deep insights and actionable recommendations related to testing and quality for Energy and Utilities. A successful candidate will be both technically strong and business savvy, with a passion to make an impact through his/her high product testing technique with timely actions.

Roles and 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.

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 :

- Apache Spark / PySpark

- Apache Airflow

- Talend / SSIS / other ETL tools

- MongoDB

- Azure / AWS / GCP

- Azure Databricks / Delta Lake / Data Lake

- Kafka or other streaming technologies

- CDC / incremental data processing

- 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.

Key Competencies :

- 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

Preferred Qualifications :

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

Skills

Data Engineering, ETL, Big Data, Python, Data Pipeline, SQL, Data Modeling, Data Integration, PySpark, Apache Spark