Python Developer – Snowflake, ETLELT, Advanced SQL & Cloud Data Engineering

Synechron is seeking a Senior Python Developer with Snowflake expertise to build optimize and support scalable cloud-based data solutions. The role focuses on Python development Snowflake data warehousing ETL/ELT pipelines SQL optimization and data integration.

Required:

• 7 years of Python development experience
• Strong Snowflake data warehouse experience
• Advanced SQL stored procedures and query optimization
• ETL/ELT pipeline development
• Pandas NumPy and PySpark
• Apache Airflow Matillion Informatica or Azure Data Factory
• AWS Azure or Google Cloud experience
• Git and REST API integration

Preferred:

• Snowflake Streams Tasks Snowpipe and dynamic tables
• dbt Docker Kubernetes and CI/CD
• Kafka or other data-streaming platforms
• Data quality and monitoring tools

• Design develop and maintain Python and Snowflake data pipelines.
• Build and optimize ETL/ELT workflows for large-scale data.
• Create Snowflake databases schemas tables views procedures streams and tasks.
• Develop data models for reporting analytics and business intelligence.
• Optimize SQL queries Snowflake warehouses clustering and compute usage.
• Integrate APIs relational databases cloud storage and external systems.
• Implement data quality security governance and compliance controls.
• Troubleshoot production issues and improve pipeline reliability.
• Collaborate with architects analysts developers and business stakeholders.
• Mentor team members and contribute to data engineering standards.

• Programming:
  Essential: Python advanced SQL scripting testing and error handling.
  Preferred: Java Scala or asynchronous Python.

• Databases/Data Management:
  Essential: Snowflake data modeling dimensional modeling schemas tables views stored procedures Streams Tasks and query tuning.
  Preferred: Snowpipe dbt NoSQL and data cataloging.

• Cloud:
  Essential: AWS Azure or Google Cloud.
  Preferred: Cloud storage Docker Kubernetes and infrastructure automation.

• Frameworks and Libraries:
  Essential: Pandas NumPy PySpark and an orchestration tool.
  Preferred: Great Expectations FastAPI Flask or Kafka.

• Development Tools:
  Essential: Git CI/CD Agile code reviews automated testing logging and monitoring.
  Preferred: Docker SonarQube infrastructure-as-code and observability tools.

• Security:
  Essential: Access control encryption secure credentials data privacy and secure API integration.
  Preferred: OAuth 2.0 OpenID Connect Snowflake masking policies and row-access policies.

• 7 years of professional Python development experience.
• Strong experience in Snowflake data engineering ETL/ELT SQL and data modeling.
• Experience integrating APIs databases cloud storage and external systems.
• Experience supporting production data platforms and resolving performance issues.
• Financial services or regulated-industry experience is preferred.
• Equivalent technical experience training or relevant projects may be considered.

• Develop Python code SQL scripts Snowflake objects and orchestration workflows.
• Build data ingestion transformation validation and publishing processes.
• Monitor pipelines data quality query performance and warehouse utilization.
• Investigate failed jobs data issues and production incidents.
• Participate in planning meetings design discussions code reviews and retrospectives.
• Collaborate with technical teams and business stakeholders.
• Prepare technical documentation and support materials.
• Make implementation decisions within approved architecture and security standards.

• Bachelors degree in computer science information technology data engineering or a related field or equivalent practical experience.
• Snowflake cloud Python or data engineering certifications are preferred.
• Completion of Synechron security compliance and role-specific training is required.
• Ongoing learning in Python Snowflake cloud technologies security and data governance is expected.

• Strong analytical and problem-solving skills.
• Clear communication with technical and non-technical stakeholders.
• Effective collaboration and mentoring abilities.
• Ability to manage priorities and meet delivery commitments.
• Adaptability to changing requirements and technologies.
• Focus on automation data quality security performance and efficient resource use.