AWS Data Engineer Job Opening in For a Client of TeamLease Digital at Hyderabad

We are looking for an experienced AWS Data Engineer with strong expertise in AWS data engineering, big data technologies, and cloud-native data platforms. The candidate will be responsible for designing, developing, and maintaining scalable data pipelines, implementing data integration solutions, and building enterprise data warehouses and data marts using AWS Redshift.

The ideal candidate should have hands-on experience with Python, PySpark, Apache Spark, Kafka, MQTT, and Airflow orchestration, along with strong SQL and data modeling skills.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using AWS cloud services.

• Build and optimize data processing workflows using Python, PySpark, and Apache Spark.

• Develop and manage enterprise data warehouses and data marts using Amazon Redshift.

• Implement real-time and streaming data ingestion pipelines using Apache Kafka and MQTT.

• Develop and manage ETL/ELT workflows for integrating data from multiple sources.

• Implement workflow orchestration and scheduling using Apache Airflow.

• Design and maintain analytical data models to support business intelligence and reporting.

• Write complex SQL queries and optimize database performance.

• Work with cloud-native AWS technologies to build reliable, scalable, and high-performance data solutions.

• Ensure data quality, consistency, security, and pipeline reliability.

• Collaborate with architects, analysts, and cross-functional teams to deliver data engineering solutions.

Required Skills & Technical Expertise

• Strong hands-on experience in AWS Data Engineering.

• Good experience with Python and PySpark programming.

• Strong knowledge of Apache Spark and distributed data processing.

• Experience with Amazon Redshift, enterprise data warehouses, and data marts.

• Hands-on experience with Apache Kafka and MQTT for data streaming and ingestion.

• Experience in Apache Airflow for workflow orchestration and pipeline scheduling.

• Strong SQL skills, including query writing and performance optimization.

• Experience in ETL/ELT development and analytical data modeling.

• Understanding of cloud-native architecture and scalable data pipeline design.

Good to Have

• Experience with AWS services such as S3, Glue, Lambda, EMR, Kinesis, and CloudWatch.

• Knowledge of data lake and data lakehouse architectures.

• Experience with real-time data processing and event-driven architectures.

• Understanding of CI/CD, Git, and deployment automation.

• Experience with data governance, data quality, and monitoring frameworks.