Senior Data Engineer

Job description:

• Education: A bachelor's or master's degree in Computer Science, Software Engineering, Data Science, or a related field is typically required. Some companies may also consider candidates with equivalent work experience and relevant certifications in data engineering or related areas.
• Experience: A minimum of 5 years of experience in data engineering or a related field is usually required for a Senior Data Engineer role. Candidates should have a proven track record of working on data-intensive projects and handling large-scale data pipelines.
• Data Engineering Skills: Strong expertise in data engineering is essential, including experience with data ingestion, data transformation, data modeling, and data integration. Candidates should be proficient in using data engineering tools and frameworks like Apache Spark, Apache Hadoop, Apache Kafka, and others.
• Big Data Technologies: Familiarity with big data technologies and distributed computing systems is important for processing and analyzing large volumes of data efficiently. Experience with cloud-based data solutions like AWS, Azure, or Google Cloud Platform may be required depending on the company's technology stack.
• Data Warehousing: Knowledge of data warehousing concepts and experience with data warehouse design and implementation is valuable for building scalable and high-performance data solutions.
• SQL and NoSQL Databases: Proficiency in SQL and experience with both relational (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) is typically required.
• Programming Languages: Strong programming skills in languages like Python, Java, Scala, or others are important for data engineering tasks and building data pipelines.
• ETL (Extract, Transform, Load): Experience with ETL processes and tools for data extraction, transformation, and loading into data warehouses or data lakes.
• Data Quality and Governance: Understanding of data quality principles and data governance practices to ensure data integrity and compliance with data standards.
• Data Security: Knowledge of data security best practices and experience in implementing data security measures to protect sensitive information.
• Analytical and Problem-Solving Skills: Strong analytical abilities to analyze data, identify patterns, and troubleshoot data engineering issues.
• Communication and Teamwork: Good communication skills to collaborate effectively with cross-functional teams, data scientists, data analysts, and other stakeholders.
• Continuous Learning: A willingness to stay updated with the latest advancements in data engineering technologies and industry best practices.
• Project Experience: Previous experience working on complex data engineering projects and delivering data solutions is a plus.
• Leadership Skills (for senior roles): For senior positions, leadership skills and the ability to mentor and guide junior data engineers may be required.