Data Engineer

Responsibilities

• Create and implement data integration solutions using a range of tools and technologies.
• Work with business units and Data Architects to define data requirements and create technical specifications.
• Partner with teams on data-centric projects and document integration processes and procedures in line with organizational standards.
• Analyze data to identify patterns and relationships crucial for integration.
• Maintain security of confidential and proprietary information.
• Develop jobs that interact with APIs or SFTP sites.
• Design and manage ETL (extract, transform, load) processes to consolidate data into a centralized repository.
• Configure and maintain data integration tools and platforms.
• Oversee data integration jobs and resolve issues as they arise.
• Enhance integration processes for better performance and scalability.
• Stay updated on new technologies and methodologies in data integration.

Skillset

• Bachelor’s degree in Computer Science, Engineering, or a related field. This foundational education provides the necessary technical background and problem-solving skills required for the role.
• At least 3 years of hands-on experience with data integration tools and processes.
• This includes experience with:
  • ETL/ELT Processes: Development and management of ETL (extract, transform, load) processes.
  • Data Warehousing: Understanding and implementation of data warehousing principles.
  • Data Integration Tools: Practical experience with data integration tools (e.g., Talend, SSIS, etc.).
  • Experience with the following technical skills:
  • Database Experience: Proficiency with SQL and at least one major relational database (e.g., Oracle, MySQL, MS SQL Server).
  • Programming: Strong programming skills in Java, Python, or similar languages relevant to data integration and manipulation.
  • Data Visualization: Experience with data visualization tools such as Tableau or Power BI.
  • Proven ability to perform data analysis, identify patterns, and troubleshoot complex data integration issues.
  • Demonstrated experience in documenting data integration processes and collaborating effectively with teams and subject matter experts.
  • Data Analysis: Strong capability to analyze data, identify patterns, trends, and relationships, and translate findings into actionable data integration strategies.
  • Problem-Solving: Exceptional analytical skills with the ability to troubleshoot and resolve issues related to data integration processes, ETL sessions, workflows, and logs.
  • Solution Design: Competence in designing, developing, testing, and deploying data integration solutions that meet business needs and technical specifications.
  • ETL Processes: Experience in developing and managing ETL processes to ensure efficient data movement from disparate sources to centralized repositories.
  • Tool Configuration & Maintenance: Skills in configuring and maintaining data integration tools and platforms to ensure their optimal performance.
    Performance Optimization: Ability to optimize data integration processes for better performance and scalability.
  • Team Collaboration: Ability to work effectively with business stakeholders, Data Architects, and other teams on data-related projects.
  • Communication Skills: Strong verbal and written communication skills to document processes, present findings, and collaborate with subject matter experts and team members.
  • Technology Awareness: Keep abreast of new data integration technologies and approaches to continuously improve integration processes.
  • Learning Agility: Demonstrated aptitude for quickly learning and adapting to new software and systems as required by evolving data needs.
  • Detail Orientation: Strong attention to detail in both data analysis and documentation to ensure accuracy and completeness.
  • Standards Compliance: Adherence to organizational standards and best practices for data management and integration.