We are looking for an experienced AWS Data Engineer (ETL & DWH) with strong hands-on expertise in AWS cloud services, data ingestion, ETL pipeline development, and data warehousing.

The ideal candidate will have experience building scalable data pipelines, transforming and integrating data from multiple sources, and maintaining data quality and governance using modern data engineering technologies.

Candidates should have strong programming skills in Python and PySpark, along with practical experience using AWS Glue, Glue Data Catalog, Amazon S3, and Amazon Redshift.

Key Responsibilities

- Perform conceptual analysis, data analysis, and problem-solving to support business requirements.
- Take ownership of data engineering initiatives and translate business requirements into effective technical solutions.
- Collaborate with subject matter experts, business analysts, data analysts, and other stakeholders to ensure effective data integration and alignment.
- Identify suitable data sources, data mapping strategies, and underlying business models.
- Develop and maintain data ingestion pipelines to collect data from databases, delimited files, and other sources.
- Perform complex data transformations and load processed data into Amazon S3.
- Develop and maintain AWS Glue jobs, mappings, and the AWS Glue Data Catalog.
- Design, develop, and optimize ETL pipelines and data warehouse solutions using Python, PySpark, and Amazon Redshift.
- Ensure data quality, accuracy, consistency, cleanliness, and reliability across multiple data sources.
- Create standardized data deliverables in accordance with corporate data standards and definitions.
- Implement and support Change Data Capture (CDC)



and event streaming technologies.
- Evaluate and support modern data formats and technologies, including Parquet and Apache Iceberg.
- Work with unstructured data processing solutions where required.
- Troubleshoot data pipeline issues and improve data processing efficiency and reliability.

Required Skills and Qualifications
- 4–6 years of overall experience in data engineering.
- At least 2–3 years of strong hands-on experience in data ingestion, ETL, and data warehousing.
- Strong hands-on experience with AWS cloud services for data management and governance.
- Proficiency in Python and PySpark for data processing and transformation.
- Practical experience with:
- AWS Glue
- AWS Glue Data Catalog
- Amazon S3
- Amazon Redshift
- Strong understanding of ETL processes, data integration, and data warehouse technologies.
- Experience designing and implementing scalable data pipelines.
- Knowledge of Change Data Capture (CDC) and event streaming technologies.
- Familiarity with Parquet, Apache Iceberg, and unstructured data processing.
- Solid analytical, problem-solving, and data management skills.
- Excellent communication and collaboration skills.

Preferred Technical Knowledge
- AWS data engineering best practices.
- Data quality validation and governance.
- Data mapping and standardization.
- ETL pipeline monitoring and optimization.
- Modern data architecture and scalable data processing solutions.

Pay: ₹600,000.00 - ₹1,200,000.00 per year

Application Question(s)

- By applying, you agree that your resume and personal details may be stored securely for up to 2 years for recruitment purposes.

Work Location: Hybrid remote in Gurgaon, Haryana 122022

📌 AWS Data Engineer (ETL & DWH) (Gurugram)
🏢 Ananta Services
📍 Gurugram