ETL Engineer

Location: Hybrid in St Louis, MO Job Type: Contract-to-hire Company: The name of our partner organization will be disclosed during the interview process.

This is not a direct role with LaunchCode; it is a position through LaunchCode, working with one of our partner companies.Disclaimer: We are unable to provide work sponsorship for this role.

We are unable to consider candidates for this role who have a current or future work sponsorship need (this includes those holding extended OPT Visas).

The Data Engineer / ETL Developer designs, builds, and supports reliable data pipelines that move and transform information from source systems into curated data platforms for reporting, analytics, operational insights, and cloud management use cases.

This role is primarily aligned to AWS-based data engineering, while also supporting the organization's expanding ownership and use of Azure data and cloud services.

The role sits at the intersection of Cloud Services and Data & Analytics, partnering with business stakeholders, analysts, architects, application teams, and platform teams to deliver trusted, scalable, secure, and cost-aware data solutions.

The position is expected to first understand what stakeholders are trying to accomplish, clarify requirements and data needs, and then work with the appropriate technical and business partners to translate those needs into well-designed data pipelines and integration patterns.

This role contributes across the full data lifecycle, including ingestion, transformation, orchestration, data quality, monitoring, documentation, and normal-hours production support.

It is expected to support timely troubleshooting, root-cause analysis, and continuous improvement during normal support hours, without creating an after-hours emergency response expectation for dashboard or reporting issues.

KEY RESPONSIBILITIES Design, develop, and maintain batch and near-real-time ETL/ELT pipelines across AWS, Azure, and on-premises data sources, applying robust transformation logic, scalable engineering patterns, and reusable development practices.

Partner directly with stakeholders to understand business objectives, reporting needs, operational questions, and pain points before moving into technical design.

Work with architects, analysts, application teams, and platform teams to clarify requirements and translate them into source-to-target mappings, technical designs, and production-ready data workflows.

Build and support pipelines using the tooling already in use across the environment, including AWS Glue, AWS Lambda, AWS Step Functions, dbt, Snowflake, PostgreSQL, S3, Athena, SQL, Python, PySpark, APIs, and related AWS technologies.

Implement data quality checks, validation routines, reconciliation processes, logging, and monitoring to ensure accuracy, completeness, timeliness, and traceability of enterprise data assets.

Troubleshoot pipeline failures, data issues, and job performance problems during normal support hours.

Improve reli...