AWS DATA ENGINEER & ETL EXPERT ( FREELANCE REMOTE )

We are looking for part time Freelancer for AWS Data Engineer Position.

Releavant Exp

9+

Mandatory Tech Stack required

Source

Salesforce (ECRM & OSC)

Backup

Grax

Cloud

AWS (EC2, S3, CloudWatch, DynamoDB, RDS, Secrets Manager, ALB, ASG)

Infrastructure as Code

Terraform

File Format

Parquet

Target

Enterprise Data Lake (EDL)

Schema

Blue Schema

Database

Blue Database

Query Language

SQL

JD

• Build and maintain AWS data pipelines
• Develop ETL/ELT pipelines using AWS Glue, PySpark, Python, and SQL.
• Ingest data from sources like Salesforce, databases, APIs, and S3.
• Load curated data into Amazon Redshift and data lake storage.
• Optimize Athena and data lake performance
• Convert JSON/CSV data into Parquet.
• Use Snappy compression.
• Design proper partitioning strategies.
• Resolve split limit and performance issues.
• Optimize Athena query costs.
• Manage modern data lake architecture
• Work with Apache Iceberg tables.
• Perform migrations from traditional Parquet tables.
• Support schema evolution, time travel, and ACID transactions.
• Production support and troubleshooting
• Investigate Glue jobs that suddenly become slow.
• Debug Lambda timeouts.
• Fix missing records and data quality issues.
• Resolve Redshift performance problems.
• Perform root cause analysis (RCA).
• Infrastructure as Code
• Build AWS infrastructure using Terraform.
• Create reusable modules.
• Manage Auto Scaling Groups, ALBs, IAM, Lambda, Secrets Manager, S3, Redshift, and DynamoDB.
• Troubleshoot Terraform state and production deployment issues.
• Security
• Manage AWS Secrets Manager.
• Configure Lambda-based secret rotation.
• Ensure Terraform does not overwrite rotated passwords.
• Implement IAM least-privilege access.
• Backup and Disaster Recovery
• Work with enterprise backup tools like Rubrik (their environment may use Grax for Salesforce).
• Validate backup jobs.
• Perform restores.
• Support disaster recovery testing.
• Verify restored data.
• Data Quality
• Validate source and target record counts.
• Maintain audit/control tables (for example in DynamoDB).
• Check checksums and duplicate records.
• Troubleshoot data discrepancies reported by business users.
• AWS Services
• S3
• Glue
• Athena
• Lambda
• Redshift
• DynamoDB
• EventBridge
• Step Functions
• CloudWatch
• Secrets Manager
• IAM
• Auto Scaling Groups
• Application Load Balancer