Data Engineer

Key Responsibilities:

• Data Pipeline Development:

  • Design and implement scalable data pipelines to collect, process, and store data for analytic use.
  • Ensure data integrity and consistent data flow across various sources and systems.
  • Automate data loading and transformations using ETL tools and frameworks.

• Data Architecture & Infrastructure:

  • Develop and optimize data storage solutions, including databases, data warehouses, and data lakes.
  • Implement robust data models and adhere to best practices in data architecture.
  • Collaborate with IT teams to ensure seamless integration and deployment.

• Collaboration & Support:

  • Work closely with data analysts, data scientists, and business stakeholders to understand data needs.
  • Provide support for data access, data visualization, and reporting tools.
  • Troubleshoot and resolve data-related technical issues swiftly and effectively.

• Security & Compliance:

  • Ensure all data processes comply with applicable data privacy laws and corporate policies.
  • Implement security measures to protect data assets and prevent unauthorized access.

• Continuous Improvement:

  • Evaluate new data engineering tools and technologies to enhance data processing capabilities.
  • Proactively identify opportunities to improve data infrastructure and processes.

Qualifications:

• Bachelor s degree in Computer Science, Engineering, Data Science, or a related field; Master s degree preferred.
• Minimum of 3 years of experience in data engineering, data warehousing, or a similar role.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with ETL tools and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Strong understanding of SQL and database design concepts.
• Excellent problem-solving skills and attention to detail.