Sr. Data Engineer

Job Title: Data Engineer

Location: 100% Remote

Employment Type: W2 Contract, 6 Month Contract with possibility of extension

Pay Rate: $50.00 – $55.00/hour

Role Overview:

BEPC is seeking a Data Engineer to support our client by designing, building, and optimizing scalable data pipelines and architectures. This role is ideal for a technically strong professional who thrives in a collaborative environment and enjoys working with large datasets, cloud platforms, and modern data technologies to drive business insights.

Key Responsibilities:

• Design, develop, and maintain ETL pipelines for large-scale structured and unstructured data.
• Build and optimize data architectures, models, and database systems for performance and scalability.
• Develop data solutions using cloud platforms (AWS, Azure, or GCP).
• Collaborate with cross-functional teams to translate business needs into technical solutions.
• Ensure data quality, integrity, and security, especially with sensitive datasets.
• Integrate data from multiple sources including databases, APIs, and flat files.
• Support analytics and machine learning initiatives with clean, reliable datasets.
• Troubleshoot and resolve data pipeline and performance issues.
• Document systems, workflows, and processes for maintainability and knowledge sharing.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 3+ years of experience in data engineering or similar roles.
• Strong experience with ETL processes and data pipeline development.
• Proficiency in SQL and Python.
• Experience with Databricks, Apache Spark, or similar big data tools.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Strong understanding of database design and optimization.
• Experience working with large-scale and distributed data systems.
• Advanced English communication skills.

Preferred Qualifications:

• Experience with real-time data processing or streaming technologies.
• Familiarity with industrial data systems (e.g., PLCs, LabVIEW).
• Exposure to machine learning workflows or data science collaboration.
• Knowledge of data governance and compliance standards.