Data Engineer

Design, build, and maintain scalable data pipelines and ETL/ELT processes

Develop and optimize data architectures, data lakes, and data warehouses

Collect, process, and clean large datasets from various sources (structured and unstructured)

Ensure data quality, integrity, and reliability across all data systems

Collaborate with data scientists, analysts, and stakeholders to support data needs

Implement data models and database schemas to support business requirements

Monitor and troubleshoot data pipeline performance and failures

Optimize data storage and retrieval for performance and cost-efficiency

Integrate data from third-party APIs, cloud services, and internal systems

Apply best practices in data governance, security, and compliance

Automate workflows and data processing tasks using scripting and orchestration tools

Maintain documentation for data pipelines, systems, and processes

Work with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure)

Support real-time and batch data processing systems

Has 3 years of experience as an ETL Developer or Data Engineer or similar positions.

Proven experience in ETL design, development, and optimization.

Has experience handling Migration Cloud Platform.

Hands-on experience with SQL Server Integration Services (SSIS).

Strong proficiency in SQL and experience working with relational and NoSQL databases.

Experience in data integration, transformation, and data pipeline orchestration.