AWS Cloud Data Engineering.
Posted on March 4, 2025
Job Description
- Key Responsibilities:
- Design, develop, and maintain scalable and efficient data pipelines on AWS.
- Implement data ingestion, transformation, and processing using AWS services such as Glue, Lambda, Kinesis, S3, and Step Functions.
- Work with Redshift, Athena, RDS, DynamoDB, and Snowflake to optimize data storage and retrieval.
- Develop and maintain ETL workflows using AWS Glue, Apache Spark, or Python.
- Ensure data integrity, security, and compliance following best practices.
- Implement and manage CI/CD pipelines for data engineering workloads.
- Collaborate with Data Scientists, Analysts, and Business teams to understand data requirements.
- Optimize performance and cost of data pipelines and cloud storage solutions.
- Monitor and troubleshoot data workflows using CloudWatch, AWS X-Ray, and logging frameworks.
- Required Skills & Experience:
- 5-6 years of experience in AWS Cloud Data Engineering.
- Hands-on experience with AWS services like Glue, Redshift, S3, Lambda, Athena, Kinesis, and Step Functions.
- Strong programming skills in Python, PySpark, or SQL.
- Experience with data modeling, schema design, and query optimization.
- Familiarity with big data technologies such as Apache Spark, Hadoop, or Kafka.
- Knowledge of data security best practices (IAM roles, encryption, VPCs, etc.).
- Experience in Terraform or CloudFormation for Infrastructure as Code (IaC).
- Working knowledge of Git, Docker, and Kubernetes for deployment and version control.
- Strong problem-solving skills with a focus on automation and scalability.
- Preferred Qualifications:
- AWS Certified Data Analytics � Specialty or Solutions Architect � Associate.
- 6 Months Contract + Extendable
- Location- Remote
Required Skills
python
pyspark
or sql.
aws services like glue
redshift
s3
lambda
athena
kinesis
and step functions.