Senior Data Engineer (Python/ AWS)

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms. You will work closely with data analysts, data scientists, and software engineers to develop reliable data solutions that support analytics, reporting, and business intelligence initiatives.

• Salary Package: Up to $9,000 (Basic, commensurate with experience) + AWS
• Working Hours: Mon-Fri
• Working Location: Central

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and cloud-native technologies.
• Build and optimize ETL/ELT workflows to ingest, transform, and process structured and unstructured data.
• Develop and manage data lakes, data warehouses, and data integration solutions on AWS.
• Ensure data quality, integrity, security, and governance across data platforms.
• Optimize data processing performance and troubleshoot pipeline issues.
• Collaborate with cross-functional teams to understand business and technical data requirements.
• Implement data validation, monitoring, and automated testing for data pipelines.
• Support batch and real-time data processing solutions.
• Document data architecture, workflows, and technical specifications.
• Continuously improve data engineering practices and adopt industry best practices.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
• Minimum 5 years of experience in Data Engineering or related roles.
• Strong programming experience in Python.
• Hands-on experience with AWS services such as S3, Lambda, Glue, EMR, Redshift, Athena, ECS/EKS, or Step Functions.
• Strong knowledge of SQL and relational databases.
• Experience building ETL/ELT pipelines and data integration solutions.
• Familiarity with data warehouse and data lake architectures.
• Experience with Git and CI/CD practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills

• Apache Spark, PySpark, or Databricks
• Apache Airflow or similar workflow orchestration tools
• Docker and Kubernetes
• Terraform or Infrastructure as Code
• Kafka or event-driven data streaming
• Snowflake, Redshift, PostgreSQL, or other modern data platforms
• Agile/Scrum development methodology

What's Offered

• Opportunity to work on large-scale cloud and data transformation projects.
• Exposure to modern AWS cloud technologies and data engineering best practices.
• Collaborative and fast-paced Agile environment.
• Career growth and continuous learning opportunities.