Description

Key Responsibilities

• Design, develop, and deploy scalable and robust data pipelines for seamless data integration and processing.
• Build and maintain enterprise-grade ETL/ELT frameworks, reusable libraries, and data processing solutions.
• Develop and optimize data models, semantic layers, and curated data products.
• Implement analytics engineering best practices, including coding standards, data governance, quality assurance, automation, and performance optimization.
• Participate in code reviews and contribute to continuous improvement of engineering standards and methodologies.
• Monitor, troubleshoot, and maintain data pipelines to ensure reliability, availability, and performance.
• Design and implement CI/CD pipelines to streamline deployment, testing, and maintenance processes.
• Collaborate with Data Scientists, Analysts, Product Managers, Engineers, and Business Stakeholders to translate business requirements into scalable technical solutions.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• Support Advanced Analytics, Business Intelligence, and AI initiatives through high-quality data engineering solutions.

Required Skills & Qualifications

• 10+ years of professional experience in Data Engineering, Analytics Engineering, or related fields.
• Strong hands-on experience with:
  • SQL
  • Python
  • dbt
  • Snowflake
  • Apache Airflow
  • Git / Version Control Systems
• Proven experience designing and building scalable data pipelines and modern data architectures.
• Strong expertise in ETL/ELT development and data integration from multiple enterprise data sources.
• Deep understanding of data warehousing concepts and data modeling techniques.
• Experience with CI/CD tools and deployment workflows.
• Strong knowledge of data governance, data quality, and performance optimization.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to work effectively in a collaborative and fast-paced environment.
• Experience supporting Business Intelligence, Data Science, Advanced Analytics, or AI/ML initiatives.

Mandatory Screening Criteria

• Minimum 10+ years of experience.
• LinkedIn profile must be verified using a work email.
• Strong recent experience with Snowflake, dbt, Python, SQL, and Airflow is required

Key Skills

Education

Bachelor's degree