Key Responsibilities:
Design and build scalable, reliable, and efficient data pipelines using Python, SQL, AWS, and Linux.
Develop and maintain data warehouses and other data-related infrastructure.
Collaborate with data scientists, analysts, and other stakeholders to ensure that data engineering solutions meet business requirements.
Mentor and train team members to ensure high-quality deliverables.
Continuously drive innovation and best practices in data engineering.
Collaborate with cross-functional teams to identify and resolve data-related issues.
Perform code reviews and ensure code quality.
Provide technical guidance and leadership to the team.
Qualifications:
Bachelor's or Master's degree in Computer Science or related field.
3-5 years of experience in data engineering, with a focus on designing and building scalable, reliable, and efficient data pipelines.
Strong expertise in Python and SQL.
Experience with AWS services such as S3, Redshift, Glue, and EMR.
Strong Linux skills.
Experience with distributed systems and big data technologies such as Hadoop, Spark, and Kafka.
Experience leading and mentoring a team of data engineers.
Excellent communication and interpersonal skills.
Ability to work in a fast-paced environment and manage multiple priorities.
Strong problem-solving skills and attention to detail.
Solid understanding of programming SQL objects (procedures, triggers, views, functions) in SQL Server. Experience optimizing SQL queries a plus.
Working Knowledge of Azure Architecture, Data Lake
Advanced understanding of T-SQL, indexes, stored procedures, triggers, functions, views, etc.
Must be detail-oriented. Must work under limited supervision. Must demonstrate good analytical skills as it relates to data identification and mapping and excellent oral communication skills.