Operations Tech Lead
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Job Location:
Monthly Salary:
Posted on:
7 hours ago
Vacancies:
1 Vacancy
Job Summary
Key Responsibilities:
Lead Operations for DWH Projects: Manage day-to-day operations for data
warehouse systems and pipelines. Ensure high availability performance and
reliability of data platforms.
Technical Leadership: Provide guidance on DBT transformations Snowflake
architecture and Power BI reporting. Review and optimize SQL queries DBT
models and data flows.
Monitoring & Incident Management: Implement monitoring tools and processes for
proactive issue detection. Troubleshoot and resolve data pipeline failures and
performance bottlenecks.
Process Improvement: Drive automation for operational tasks and deployments.
Establish best practices for version control CI/CD and data quality checks.
Collaboration: Work closely with Data Engineers BI Developers and Business
Analysts. Communicate effectively with stakeholders on project status and
operational metrics.
Required Skills & Experience:
Technical Expertise: Strong hands-on experience with DBT (data modeling
transformations). Proficiency in Snowflake (warehousing concepts performance
tuning). Experience with Power BI (reporting dashboards DAX).
Data Engineering & Operations: Knowledge of ELT/ETL pipelines and orchestration
tools (Airflow preferred). Familiarity with CI/CD for data projects and Git-based
workflows.
Other Skills: Strong SQL skills and understanding of data warehousing principles.
Excellent problem-solving and analytical abilities. Good communication and
leadership skills.
Nice-to-Have:
Experience with cloud platforms (Azure).
Knowledge of data governance security and compliance.
Exposure to Python for scripting and automation.
Lead Operations for DWH Projects: Manage day-to-day operations for data
warehouse systems and pipelines. Ensure high availability performance and
reliability of data platforms.
Technical Leadership: Provide guidance on DBT transformations Snowflake
architecture and Power BI reporting. Review and optimize SQL queries DBT
models and data flows.
Monitoring & Incident Management: Implement monitoring tools and processes for
proactive issue detection. Troubleshoot and resolve data pipeline failures and
performance bottlenecks.
Process Improvement: Drive automation for operational tasks and deployments.
Establish best practices for version control CI/CD and data quality checks.
Collaboration: Work closely with Data Engineers BI Developers and Business
Analysts. Communicate effectively with stakeholders on project status and
operational metrics.
Required Skills & Experience:
Technical Expertise: Strong hands-on experience with DBT (data modeling
transformations). Proficiency in Snowflake (warehousing concepts performance
tuning). Experience with Power BI (reporting dashboards DAX).
Data Engineering & Operations: Knowledge of ELT/ETL pipelines and orchestration
tools (Airflow preferred). Familiarity with CI/CD for data projects and Git-based
workflows.
Other Skills: Strong SQL skills and understanding of data warehousing principles.
Excellent problem-solving and analytical abilities. Good communication and
leadership skills.
Nice-to-Have:
Experience with cloud platforms (Azure).
Knowledge of data governance security and compliance.
Exposure to Python for scripting and automation.
