Data Engineer

Role Overview

We are seeking an experienced Manager – Data Engineering to lead the design, automation, governance, and optimization of enterprise data pipelines and modern data warehouse solutions. The ideal candidate will have strong expertise in ETL modernization, Snowflake environments, data quality controls, vendor integrations, and stakeholder collaboration to support executive reporting and business intelligence.

This role requires both hands-on technical capability and team leadership , ensuring scalable, reliable, and governed data ecosystems.

Key Responsibilities

1. Data Architecture & ETL Modernization

• Lead the transition from manual or legacy data processes to automated, scalable ETL frameworks.
• Design, build, and maintain robust ingestion pipelines using tools such as Informatica.
• Migrate and centralize transformation workflows to improve processing efficiency, scalability, and maintainability.
• Architect structured staging and transformation layers within Snowflake data warehouses.

2. Data Ingestion & Integration

• Manage end-to-end ingestion of financial and operational datasets from internal systems and vendor-hosted SFTP environments.
• Develop automated ingestion frameworks with post-load validation and structured data quality checks.
• Ensure reliable, secure, and governed data integration across multiple sources.

3. Data Quality, Governance & Monitoring

• Implement data validation frameworks, KPI monitoring, and anomaly detection mechanisms.
• Reduce vendor-related data incidents through proactive monitoring and root cause analysis.
• Establish best practices for data governance, documentation, and compliance.
• Maintain data integrity before downstream reporting and dashboard consumption.

4. Business Intelligence & Stakeholder Collaboration

• Partner with business stakeholders to ensure accurate executive reporting and evolving KPI alignment.
• Support and enhance Tableau dashboards by refining calculations, updating data models, and maintaining reporting logic.
• Act as the primary liaison between business users, vendors, and technical teams to resolve discrepancies and production issues.

5. Leadership & Team Development

• Mentor and guide data engineers on ETL best practices, automation, and data quality standards.
• Drive continuous improvement initiatives across data engineering processes.
• Promote scalable design patterns and performance optimization strategies.

Required Skills & Experience

• 5+ years of experience in Data Engineering or related roles.
• Proven experience with:
• Snowflake data warehouse environments
• Informatica (or similar ETL tools)
• SQL (advanced querying & performance optimization)
• Data modelling & data warehousing concepts
• SFTP-based data integrations
• Experience migrating legacy transformation tools (e.g., Alteryx) to centralized ETL platforms.
• Strong understanding of data governance, validation frameworks, and quality controls.
• Experience supporting BI tools such as Tableau.
• Proficiency in Python for data processing and automation.
• Experience working with ERP and CRM data sources is preferred.
• Exposure to Databricks or modern data lake architectures is a plus.

Education

• Bachelor’s degree in Computer Science, Data Science, or related field (Master’s preferred).