Hybrid Data Engineer Data Engineer with verification

✅ Key responsibilities:

• Data Architecture: Design and maintain data architecture across data lakes, databases, and data warehouses.
• Pipeline Development: Build and deploy efficient data pipelines and ETL/ELT processes using industry-standard tools.
• Collaboration: Work closely with client stakeholders to align on project goals, manage expectations, and provide data-driven solutions.

✅ Requirements:

• Experience in Data Engineering: Background in data pipeline development, data management, and ETL processes.
• Programming Skills: Proficiency in one or more programming languages, such as Python, SQL, R, JavaScript, Java, or Scala.
• Cloud Knowledge: Familiarity with Cloud platforms (Azure, AWS, or GCP) and Cloud architecture principles.
• Data Tools: Exposure to tools and technologies such as Databricks, Snowflake, Redshift, or similar for data warehousing.
• Data Visualization: Knowledge of data visualization tools like Power BI or Tableau is advantageous.
• Adaptability & Curiosity: Willingness to work across diverse technologies and an eagerness to continue learning and adapting.

✅ What we offer:

• Flexible work environment, with options for remote work.
• Professional development opportunities and training support.
• A comprehensive benefits package tailored to your needs.
• A collaborative team that values innovation and growth.

If you’re ready to tackle new challenges, click 'Apply' and start your journey with us!