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.
Job Requirement
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.
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