Data Engineer

Technical Skills Required:

• ETL Concepts:
• Strong understanding of Extract, Transform, Load (ETL) processes
• Ability to design, develop, and maintain robust ETL pipelines
• Database Fundamentals:
• Proficiency in working with relational databases (eg, MySQL, PostgreSQL, Oracle, or MS SQL Server)
• Knowledge of database design and optimization techniques
• Basic Data Visualization:
• Ability to create simple dashboards or reports using visualization tools (eg, Tableau, Power BI, or similar)
• Query Optimization:
• Expertise in writing efficient, optimized queries to handle large datasets
• Testing and Documentation:
• Experience in validating data accuracy and integrity through rigorous testing
• Ability to document data workflows, processes, and technical specifications clearly

Key Responsibilities:

• Data Engineering Tasks:
• Design, develop, and implement scalable data pipelines to support business needs.
• Ensure data quality and integrity through testing and monitoring.
• Optimize ETL processes for performance and reliability.
• Database Management:
• Manage and maintain databases, ensuring high availability and security.
• Troubleshoot database-related issues and optimize performance.
• Collaboration:
• Work closely with data analysts, data scientists, and other stakeholders to understand and deliver on data requirements.
• Provide support for data-related technical issues and propose solutions.
• Documentation and Reporting:
• Create and maintain comprehensive documentation for data workflows and technical processes.
• Develop simple reports or dashboards to visualize key metrics and trends.
• Learning and Adapting:
• Stay updated with new tools, technologies, and methodologies in data engineering.
• Adapt quickly to new challenges and project requirements.

Additional Requirements:

• Strong communication skills, both written and verbal.
• Analytical mindset with the ability to solve complex data problems.
• Quick learner and willingness to adopt new tools and technologies as needed.
• Flexibility to work in shifts, if required.

Preferred Skills (Not Mandatory):

• Experience with cloud platforms (e.g., AWS, Azure, or GCP).
• Familiarity with big data technologies such as Hadoop or Spark.
• Basic understanding of machine learning concepts and data science workflows.