Key Responsibilities

  • Design, build, and maintain scalable ETL/ELT pipelines to integrate data into Snowflake.
  • Write, optimize, and maintain SQL scripts for transformations, performance tuning, and troubleshooting.
  • Monitor ETL/ELT pipelines for failures, latency, and data quality issues; triage issues with stakeholders and communicate resolution timelines.
  • Document data workflows, schema changes, and operational procedures.
  • Manage Snowflake data warehouse, including monitoring storage usage, query performance, cost optimization, and warehouse health.
  • Implement and manage role-based access control (RBAC), row-level security, and data masking to protect sensitive data.
  • Implement CI/CD workflows for pipelines, transformations, and reporting assets (e.g., GitHub Actions, Azure DevOps, Jenkins).
  • Use dbt to manage and version-control data transformations.
  • Develop and maintain Power BI dashboards and data models, ensuring accuracy, usability, and performance.
  • Troubleshoot and enhance dashboards/reports for speed, clarity, and usability.
  • Maintain and improve alerting systems for pipeline or data integrity issues.
  • Implement basic changes to pipelines (e.g., updating sources, adjusting transformations).
  • Integrate monitoring and alerting via Snowflake Account Usage views and/or external observability tools (Datadog, CloudWatch, Azure Monitor).
  • Orchestrate workflows with tools such as Airflow, Prefect, or similar.
  • Support data governance efforts by documenting lineage, transformations, and metadata.


Qualifications
  • Minimum 5 years of experience in data engineering or a related field.
  • Strong expertise in SQL and Snowflake (query optimization, cost/performance tuning, warehouse scaling).
  • Proven experience with ETL/ELT pipelines, automation, and data quality practices.
  • Hands-on experience with Power BI (DAX, Power Query, modeling, row-level security).
  • Experience implementing and managing RBAC and data security controls in Snowflake.
  • Familiarity with orchestration tools (Airflow, Prefect, Dagster, or equivalent).
  • Experience with CI/CD workflows for data.
  • Familiarity with dbt for managing transformations.
  • Basic scripting experience (Python or equivalent) for automation and API integrations.
  • Experience with GitHub or similar version control tools to manage changes and ensure codebase stability.
  • Familiarity with cloud data ecosystem services (AWS S3, Azure Blob, GCP Storage, IAM).
  • Strong problem-solving and troubleshooting skills.
  • Excellent communication skills to work with both technical and non-technical stakeholders. 

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