Jeavio - Senior Data Engineer - Data Integration (5-7 yrs)

Key Responsibilities :

Data Integration Development :

- Design, develop, and maintain robust data integration pipelines between our internal systems and external vendors using ETL tools and APIs.

- Integrate disparate data sources and ensure seamless data flow across internal and external platforms.

- Develop solutions to improve data integration efficiency and enhance data accessibility.

Collaboration with Product Teams :

- Work closely with internal product teams to understand business requirements and deliver data solutions that are scalable and reliable.

- Ensure data consistency and integration alignment across different platforms by closely collaborating with cross-functional teams.

Data Workflow Optimization :

- Monitor, optimize, and maintain data workflows to ensure high performance, reliability, and scalability of integration processes.

- Troubleshoot and resolve data integration issues promptly to minimize disruptions and ensure continuous operations.

Data Quality and Validation :

- Implement data quality checks and validation processes to ensure the accuracy and completeness of integrated data.

- Continuously improve data integration practices to ensure that only clean and validated data enters the system.

Documentation and Knowledge Sharing :

- Document all data integration processes, workflows, and best practices to ensure knowledge sharing and effective onboarding of new team members.

- Create clear documentation that details data flow, error-handling procedures, and other integration-related processes.

Stay Current with Industry Trends :

- Keep up-to-date with the latest trends, technologies, and best practices in data integration and engineering.

- Recommend and implement improvements to existing integration systems and workflows, leveraging new tools and technologies to enhance performance and scalability.

Security, Governance, and Compliance :

- Ensure data governance standards and compliance requirements are met during the data integration process.

- Implement security measures to protect sensitive data and ensure compliance with data protection regulations.

Required Qualifications and Skills :

Experience :

- 5+ years of experience as a Data Engineer with a strong focus on data integration.

- Proven experience with ETL processes, integrating systems, and working with APIs for data exchange.

- In-depth experience with SQL and NoSQL databases (e.g, PostgreSQL, SQL Server, MongoDB, Oracle), including performance tuning and optimization.

- Experience with cloud platforms, particularly AWS, for building scalable and reliable data integration solutions.

Technical Expertise :

- Proficiency in using ETL tools such as Apache NiFi, Talend, Informatica, Fivetran, or custom ETL pipelines.

- Strong programming skills in languages such as Python, JavaScript, PowerShell (experience with Python is highly preferred).

- Experience with API development and integration, ensuring seamless data communication between platforms.

- Familiarity with data warehousing concepts and architectures, such as Star Schema, Snowflake Schema, and ETL pipelines for large-scale data storage.

- Experience in data modeling and schema design to ensure that data is structured and stored effectively for analytics and reporting.

Data Governance & Compliance :

- Understanding of data governance principles, data protection standards, and regulatory compliance (e.g, GDPR, HIPAA).

- Ability to apply data security best practices to ensure the confidentiality, integrity, and availability of data.

Problem-Solving and Troubleshooting :

- Strong problem-solving skills and ability to troubleshoot complex data integration issues.

- Ability to quickly identify issues, resolve problems, and ensure the smooth functioning of data integration processes.

Collaboration and Communication :

- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.

- Experience with Agile methodologies and working in an Agile environment, ensuring flexibility and quick delivery of integration solutions.

Version Control and Tools :

- Familiarity with version control systems such as Git to manage code and configuration.

- Experience with automation tools and scripting for data pipeline management.

Certifications :

- Relevant certifications in Data Engineering, Cloud Platforms (e.g, AWS Certified Data Analytics - Specialty), or Integration Tools are a plus.

- Certifications in ETL tools or cloud platforms like AWS or Azure are desirable.

Preferred Skills :

- Experience with containerization technologies (e.g, Docker, Kubernetes) for deploying and managing data pipelines.

- Familiarity with Big Data technologies such as Hadoop, Spark, or Kafka is a plus.

- Knowledge of ERP systems and business process integration.

- Familiarity with DevOps practices and integrating CI/CD pipelines for automated testing and deployment of data solutions.

Education :

- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field