StatusNeo - AWS Data Engineer - Python/PySpark
Posted on: 29/05/2026
Job Description
Description :
We are looking for a highly skilled Data Engineer to design, build, and maintain scalable data pipelines and cloud based data platforms. The ideal candidate should have strong experience in cloud data engineering, big data technologies, ETL/ELT pipelines, and data warehousing, and should be comfortable working in a hybrid work environment (3 days WFO) at our Gurgaon office.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines using cloud and big data technologies
- Build and optimize ETL/ELT workflows for batch and real time data processing
- Implement data solutions on AWS / Azure / GCP cloud platforms
- Work extensively with Spark / PySpark for large scale data transformations
- Develop and maintain data integrations using tools like AWS Glue, Datastage, Informatica, and Airflow
- Handle streaming data pipelines using Kafka / AWS Kinesis
- Manage and optimize data warehouses such as Snowflake and AWS Redshift
- Perform database migrations using AWS Database Migration Service (DMS)
- Work with SQL and NoSQL databases (MSSQL, MySQL, DynamoDB, Cassandra, HDFS, etc.)
- Collaborate with BI teams to support analytics and reporting using Power BI / Tableau
- Ensure data quality, performance tuning, logging, monitoring, and security best practices
- Participate in architecture discussions and mentor junior engineers when required
Required Skills & Qualifications :
Must-Have :
- 5+ years of experience as a Data Engineer / Big Data Engineer
- Strong expertise in Python and PySpark
- Hands on experience with Apache Spark
- Solid understanding of SQL and complex query optimization
- Practical experience with AWS cloud services, including :
1. S3, Glue, Athena, EMR, Lambda
2. AWS Managed Apache Airflow
3. AWS DMS
- Experience working with Snowflake and/or AWS Redshift
- Strong knowledge of data modeling and warehousing concepts
Good to Have / Preferred Skills :
- Experience with Azure or GCP (Dataflow, BigQuery, etc.)
- Streaming platforms : Kafka, AWS Kinesis
- Hadoop ecosystem : HDFS, MapR
- NoSQL databases : DynamoDB, Cassandra, Datastax
- Exposure to graph databases like JanusGraph, ArangoDB
- BI tools : Power BI, Tableau
- Experience with CI/CD for data pipelines
- Knowledge of data governance and security best practices
Work Mode & Location :
- Hybrid model : 3 days work from office
- Office location : Gurgaon
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Posted by
110
Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1640145
