AWSCloudETLKafkaPythonSQLTerraformAIClaudeData EngineeringData WarehousingAnalyticsSnowflakeDatabricksAmazon Web ServicesDatadogAgileRemote Work
About this role
Role Overview
Build scalable, high-performance data infrastructure that transforms complex transactional and financial data into trusted datasets for regulatory reporting and business operations.
Develop reliable data pipelines and data products that power regulatory reporting, financial operations, analytics, and operational insights while ensuring data accuracy and reliability.
Design, build, and optimize modern data models and distributed data pipelines.
Leverage AI throughout the software development lifecycle to improve engineering productivity, strengthen data quality, and build trusted data products.
Collaborate with cross-functional stakeholders to translate complex business and regulatory requirements into scalable, analytics-ready data models and solutions.
Mentor Data Engineering teammates by sharing best practices, providing technical guidance, and helping raise engineering standards across the team.
Collaborate in an agile environment to deliver scalable data solutions that support evolving business and regulatory needs.
Requirements
At least 3 years of experience designing, building, and maintaining scalable data platforms and distributed data systems.
Strong proficiency in Python and SQL, with hands-on experience developing both real-time and batch data processing solutions.
Experience with modern cloud-based data platforms using technologies such as Snowflake, Databricks, Kafka, or similar distributed data processing and streaming technologies.
Experience with cloud infrastructure, preferably Amazon Web Services (AWS), as well as tools such as Terraform, Datadog, and PagerDuty.
A strong understanding of data warehousing, data lakes, ETL frameworks, distributed data processing, and modern data modeling techniques.
Experience building trusted data solutions that support financial operations, regulatory reporting, auditability, reconciliation, or other highly governed data domains.
Hands-on experience with AI-assisted engineering tools such as Claude Code, Codex, or similar technologies.