Data Engineer - Python/Snowflake

Join a growing data engineering team supporting mission-critical analytics and business operations within the energy, commodities trading, oil & gas, or financial services sector. This role is focused on designing and supporting cloud-based data solutions using Python, Snowflake, and AWS, enabling scalable, reliable, and high-performance data platforms. You will work closely with business stakeholders, analysts, and engineering teams to build production-grade data pipelines, modernize legacy data environments, and deliver trusted datasets that support operational and strategic decision-making.

Responsibilities

• Design, develop, and maintain scalable Python-based data pipelines that ingest, transform, and deliver data from internal and external sources.
• Build and optimize data models within Snowflake, ensuring performance, scalability, and cost efficiency.
• Develop ELT/ETL solutions leveraging cloud-native AWS services.
• Create, monitor, and support batch and near real-time data integration workflows.
• Work with structured, semi-structured, and time-series datasets from operational, trading, financial, and market data systems.
• Modernize legacy data processes and migrate legacy database workloads into modern cloud architectures.
• Implement data quality, reconciliation, monitoring, and alerting capabilities across the data platform.
• Collaborate with analysts, traders, business users, and technology teams to deliver data solutions aligned with business objectives.
• Participate in code reviews, testing, documentation, and deployment activities following engineering best practices.
• Support production environments and troubleshoot data pipeline issues as needed.

Required Qualifications

• 3+ years of hands-on experience as a Data Engineer building and supporting production data pipelines.
• Strong development experience with Python, including Pandas and related data-processing frameworks.
• Advanced SQL skills with experience in query optimization, data modeling, and performance tuning.
• Experience designing and supporting solutions within Snowflake or a comparable cloud data warehouse.
• Hands-on experience with AWS services supporting data platforms and analytics environments.
• Background building and maintaining ETL/ELT processes in a cloud ecosystem.
• Experience with workflow orchestration tools such as:
• Prefect
• Airflow
• Dagster
• Strong understanding of data engineering fundamentals, software development best practices, version control, testing, and CI/CD.
• Experience implementing monitoring, alerting, and operational support processes for production systems.
• Excellent communication skills with the ability to partner directly with business stakeholders.

Preferred Qualifications

• Experience with dbt for data transformation and modeling.
• Exposure to Kafka, Redis, Oracle, Databricks, or similar enterprise data technologies.
• Experience with Docker, Terraform, FastAPI, or cloud-native application development.
• Background supporting enterprise analytics, market data, risk management, trading, supply chain, or operational reporting platforms.