We are seeking a skilled Data Engineer to join our team and help build and maintain robust data pipelines and infrastructure. The ideal candidate will be responsible for designing, developing, and optimizing data solutions that support data analytics and business intelligence. The role requires expertise in data processing, integration, and storage technologies, and a strong ability to work with large datasets and ensure data quality and accessibility.

Key Responsibilities

• Design, build, and maintain scalable data pipelines to support data processing and analytics needs.
• Integrate data from various sources, ensuring seamless and efficient data flow across systems.
• Develop and manage data storage solutions, including databases, data warehouses, and data lakes.
• Implement data quality checks and validation processes to ensure the accuracy, consistency, and reliability of data.
• Optimize data processing workflows and storage solutions to improve performance and reduce latency.
• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Create and maintain clear documentation for data pipelines, integration processes, and data architecture.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience as a Data Engineer or in a similar role, with a strong understanding of data engineering principles.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with data processing frameworks (e.g., Apache Spark, Hadoop) and database systems (e.g., SQL, NoSQL).
• Knowledge of data warehousing solutions (e.g., AWS Redshift, Google BigQuery, Snowflake).
• Familiarity with ETL tools and data integration platforms.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.

Preferred Skills

• Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of data modeling and data architecture best practices.
• Familiarity with data visualization tools (e.g., Tableau, Power BI).

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