Data Engineer III

• Design, develop, and maintain complex data pipelines and data infrastructure, ensuring data availability, quality, and integrity.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver robust data solutions.
• Build and optimize ETL processes for extracting, transforming, and loading large datasets across various sources.
• Design and implement scalable data architectures and frameworks that support advanced analytics and machine learning applications.
• Troubleshoot, debug, and optimize existing data systems to improve performance and reliability.
• Develop and manage databases and data storage solutions, ensuring efficient data retrieval and processing.
• Ensure proper data governance, security, and compliance with industry regulations and company policies.
• Provide mentorship and guidance to junior and mid-level data engineers, fostering a culture of continuous learning and improvement.
• Stay up to date with emerging trends and technologies in the data engineering space and evaluate their potential applications.
• Work with cloud-based platforms (AWS, GCP, Azure) to manage large-scale data processing and storage.

Required Skills and Qualifications:

• Bachelor s degree in Computer Science, Information Technology, Engineering, or a related field. Master s degree is a plus.
• 5+ years of experience as a Data Engineer, with at least 2 years in a senior or Level 3 data engineering role.
• Expertise in SQL and experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).
• Strong experience with data pipeline orchestration tools (e.g., Apache Airflow, Luigi, Prefect).
• Proficiency in programming languages such as Python, Java, or Scala for data processing and automation.
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka).
• In-depth knowledge of cloud platforms (AWS, GCP, Azure) and cloud data services (e.g., Redshift, BigQuery, Databricks).
• Familiarity with data warehousing concepts and tools (e.g., Snowflake, Amazon Redshift, Google BigQuery).
• Knowledge of data modeling, data lake architectures, and data governance best practices.
• Strong problem-solving skills and the ability to work with complex data sets and systems.
• Excellent communication and collaboration skills to work with cross-functional teams.