Responsibilities

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.

Technical Skills

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.

Experience Requirements

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.

Day-to-Day Activities

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.

Qualifications

Bachelor’s 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