Data Engineer - Python

Bahwan Cybertek Group; United States; Remote; USD 110,000 - 180,000; Full time

Job summary

Bahwan Cybertek Group in the United States seeks a data engineer with 5+ years in data engineering or Python development. You will work on data pipelines, ETL/ELT processes, and data validation, leveraging AWS cloud services and modern SQL databases.

Candidates should be proficient in SQL, data transformation, and automation, with experience in distributed processing and data integration. Familiarity with PySpark, NoSQL, and containerized deployments is a plus.

Skills

Python development

Data engineering

ETL/ELT

SQL

Advanced SQL

AWS

Data pipelines

Data quality

Data integration

Tools

PySpark

DynamoDB

Cassandra

Airflow

Docker

AWS services

Job description

Required skills:

• 5+ years of experience in Data Engineering, Python development, or a related role.
• Strong hands-on expertise in Python, particularly for , Data wrangling and transformation, ETL/ELT development, File and data processing, Automation and scripting, Data validation and cleansing.
• Strong knowledge of at least one relational SQL database such as: PostgreSQL, MySQL, Oracle, SQL Server
• Strong understanding of SQL, including joins, subqueries, CTEs, window functions, aggregations, and query optimization.
• Experience with AWS cloud services used in data engineering.
• Good understanding of data engineering concepts, including data pipelines, ETL architecture, data quality, and data integration.

Good to have skills:

• Hands-on experience with PySpark and distributed data processing.
• Experience with NoSQL databases such as DynamoDB, or Cassandra.
• Experience with AWS services such as S3, Lambda, Glue, Athena, Redshift, EMR, RDS, Step Functions, Event Bridge, and CloudWatch.
• Experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions.
• Experience with Docker and containerized applications.
• Familiarity with CI/CD pipelines and DevOps practices.
• Knowledge of data warehousing and dimensional data modeling.
• Experience working with large-scale datasets and performance optimization.
• Familiarity with cloud-based data lake and data warehouse architectures.