Proficiency in dbt, Snowflake, Unix, SQL, and DataStage
Experience with data architecture design and implementation
Strong understanding of data quality and integrity
Ability to mentor and guide junior team members
Responsibilities
Lead the design and implementation of robust data architectures
Ensure the integrity and quality of data across all pipelines
Drive performance optimization for data solutions
Mentor and guide junior data engineering team members
Collaborate with various stakeholders to deliver reliable and high-performance data solutions
Develop and optimize scalable data pipelines using DBT, Snowflake, and IBM DataStage
Benefits
Opportunities for professional development and mentorship
Collaborative work environment with cross-functional teams
Access to modern data technologies and tools
Focus on performance optimization and data quality
Involvement in strategic data architecture initiatives
Full Job Description
Role Overview:
This Lead Data Engineer role focuses on designing, building, and optimizing scalable data pipelines. The position involves utilizing modern ELT and traditional ETL approaches with technologies such as DBT, Snowflake, and IBM DataStage. The successful candidate will lead data architecture initiatives, ensure high data quality, and drive performance optimization, while also mentoring team members. Collaboration with stakeholders is key to delivering reliable, high-performance data solutions for analytics and business needs.
Key Responsibilities:
Lead the design and implementation of robust data architectures.
Ensure the integrity and quality of data across all pipelines.
Drive performance optimization for data solutions.
Mentor and guide junior data engineering team members.
Collaborate with various stakeholders to deliver reliable and high-performance data solutions.
Develop and optimize scalable data pipelines using DBT, Snowflake, and IBM DataStage.
