Lead Data Engineer - Snowflake + (Datastage/BODS)

Functional Skills

• Team Player: Support peers, team, and department management.
• Communication: Excellent verbal, written, and interpersonal communication skills.
• Problem Solving: Excellent problem-solving skills, incident management, root cause analysis, and proactive solutions to improve quality.
• Partnership and Collaboration: Develop and maintain partnership with business and IT stakeholders
• Attention to Detail: Ensure accuracy and thoroughness in all tasks.

Technical/Business Skills

• Data Engineering: 10+ years of experience in designing and building Data Warehouse and Data lakes. Good knowledge of data warehouse principles, and concepts. Technical expertise working in large scale Data Warehousing applications and databases such as Oracle, Netezza, Teradata, and SQL Server. Cloud-based data platform experience especially Snowflake and AWS.
• 10+ years of experience in designing and building Data Warehouse and Data lakes. Good knowledge of data warehouse principles, and concepts.
• Technical expertise working in large scale Data Warehousing applications and databases such as Oracle, Netezza, Teradata, and SQL Server.
• Cloud-based data platform experience especially Snowflake and AWS.
• Data integration skills: Expertise in design and development of complex data pipelines Solutions using any industry leading ETL tools such as IBM Data Stage or SSIS or SAP Business Objects Data Services (BODS) Experience with Unix, Python or equivalent scripting language Basic knowledge of Transform/ELT tools such as DBT , Qlik Replicate, AWS Glue or Snowpark , etc.
• Expertise in design and development of complex data pipelines
• Solutions using any industry leading ETL tools such as IBM Data Stage or SSIS or SAP Business Objects Data Services (BODS)
• Experience with Unix, Python or equivalent scripting language
• Basic knowledge of Transform/ELT tools such as DBT , Qlik Replicate, AWS Glue or Snowpark , etc.
• Expert in SQL , stored procedures and adept in tracing and resolving data integrity issues.
• Strong knowledge of data architecture, data design patterns, modeling
• Data Model : Expertise in Logical and Physical Data Model using Relational, Dimensional or Data Vault Modeling practices with high volume ETL/ELT processes.
• Good experience with scheduling tools such as Control-M
• Performance tuning of data pipelines and DB Objects to deliver optimal performance.
• Experience in Gitlab version control and CI/CD processes.
• Experience working in Financial Industry is a plus.

Relationships & Collaboration

Accessibility Needs

Equal Employment Opportunity