Data Engineer

Key Responsibilities:

1. Design and build production-grade (ETL/ELT) pipelines using AWS services (e.g. Glue, Lambda, EMR, Step Functions.) and/or open-source solutions (e.g. Apache Spark, dbt) for various structured and unstructured data sources.
2. Design and optimize data models, schemas, and data storage architectures for analytical workloads
3. Design and implement data lake, data warehouse, and data lakehouse solutions to support data analytics platforms.
4. Build BI dashboards and analytics visualization solutions using tools such as AWS QuickSight, PowerBI, or similar tools

Requirements:

1. Bachelor's degree or higher in Computer Science or related engineering field.
2. At least 7 years of professional experience in data engineering, designing, building and operating cloud-based data platforms and analytics solutions.
3. Strong programming skills in Python and SQL with experience building scalable ETL/ELT pipelines.
4. Experience working with data warehouses, data lakes, or lakehouse architectures.
5. Experience with distributed data processing frameworks such as Spark or similar technologies.
6. Hands-on experience with data orchestration and workflow tools such as Airflow, AWS Step Functions, , or similar tools.
7. Hands-on experience of data modeling, data governance, data quality, and security best practices.
8. Experience working with cloud-based data platforms (AWS, Azure) and modern data ecosystem tools.
9. Experience in building BI dashboards using PowerBI, Amazon QuickSight, or similar tools