Senior Data Engineer

Join Omaha Insights as a Senior Data Engineer and help shape the future of financial data infrastructure. You will design, build, and maintain the data architecture that drives our financial intelligence platform. Your work will directly impact how we process, analyze, and leverage financial data to create value for our clients. You will collaborate closely with finance professionals, AI engineers, and fellow data engineers in a non-hierarchical environment.

• Designing, building, and maintaining the data architecture that drives the financial intelligence platform.
• Collaborating with AI engineers to scrape and process PDF documents, news feeds, and financial reports using Python and AI models.
• Contributing to the design and evolution of the cloud-based data architecture, optimizing data pipelines for performance, reliability, and cost efficiency.

We’re looking for someone who combines technical depth with intellectual curiosity. You should be comfortable working across multiple layers of a data system and excited about tackling the unique challenges of financial data.

**Requirements**

**Technical Skills**

• Python - you write clean, production-grade code with solid testing practices
• SQL - you can write and optimize complex queries, understand execution plans, and think about data organization
• PySpark, Spark, or Databricks - hands-on experience building distributed data processing pipelines at scale
• Cloud platforms - GCP, AWS, or Azure; comfortable with object storage, distributed compute environments, and modern data platforms
• Data pipelines & orchestration - solid understanding of ETL/ELT, Airflow (or similar orchestration tools), data quality, monitoring, and how to build reliable, maintainable systems
• Git - version control and collaborative development are second nature to you

**Experience**

• 7–15 years building and maintaining production data systems - you understand the difference between prototypes and systems that run reliably at scale
• Hands-on experience with real-world data challenges - you’ve debugged production issues, optimized slow queries, and dealt with data quality problems
• Bonus: Financial data experience (financial statements, market data, time-series analysis) — you understand the domain and can ask the right questions

**Soft Skills & Mindset**

• Problem solver - you tackle ambiguous challenges with pragmatism, iterate quickly, and learn from feedback
• Communicator - you explain technical tradeoffs clearly, listen to non-technical stakeholders, and ask insightful questions to understand what actually matters
• Owner - you take pride in code quality, testing, documentation, and operational reliability; you care about the systems you build
• Curious about finance - you want to understand how companies really work, what drives performance, and why accounting adjustments matter; you’re excited about learning financial concepts alongside building data infrastructure
• Comfortable with ambiguity - in a startup, requirements evolve and you move fast; you thrive when given autonomy to solve problems your own way

**Nice-to-Have Skills**

• Experience with financial data sources (Bloomberg, Reuters, SEC EDGAR, etc.)
• Experience scraping and processing unstructured data (PDFs, web content, etc.)
• Familiarity with AI/ML workflows and integrating model outputs into production systems
• Experience with modern data transformation and modeling tools such as dbt
• Experience with analytical databases and data warehouses such as BigQuery, Snowflake, or Redshift
• Exposure to DevOps, CI/CD, and infrastructure-as-code
• Basic understanding of financial concepts (balance sheets, cash flow, valuation metrics)