Main Purpose:
The Lead Data Engineer is responsible for leading the design, development, and maintenance of the organization's data infrastructure and data processing pipelines. They will work closely with cross-functional teams to ensure reliable, secure, and efficient data operations that support the organization's data-driven initiatives.
Key Accountabilities:
- Build and maintain the infrastructures and ETL pipelines for extraction and processing of structured and unstructured data.
- Own data operations and be responsible for data usage, quality, reliability, security and availability.
- Collaborate with stakeholders and cross-functional team to design and build data products and data services for internal consumption.
- Work with engineering and data science team to design and build services that empower optimal data-driven business operations.
- Analyze and communicate data insights to stakeholders.
- Contribute in designing and maintaining effective and highly-performing data architecture.
Requirements/Specifications:
Education: Bachelor's or master's degree in Computer Science, Information Technology, or a related field.
Experience: 7+ years of experience as a Data Engineer and 2 years of experience in a similar role.
Work-related skills:
- Experience in data architecture, quality, metadata management, ETL, analytics, reporting, and database administration.
- Strong computer science background and knowledge of software development methodologies.
- Excellent knowledge of data modeling and SQL.
- Experience with the following data tools/systems: dbt, Spark, Storm, Delta Lake, Databricks, BigQuery, PowerBI, etc.
- Familiarity with Azure Data Platform and a backend stack (Python, Go) is a plus.
Soft skills:
- Diligent, self-motivated, have a strong sense of autonomy and can work independently or with a team.
- Excellent problem-solving, critical thinking, and communication skills.
