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GreatAmerica Financial Services

Provides equipment financing and leasing solutions

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or an equivalent combination of education and relevant professional experience.
  • At least 7 years of hands-on data engineering experience building and supporting production data solutions.
  • At least 7 years of advanced SQL experience, including complex querying, data transformation, performance tuning, and high-volume processing; strong T-SQL experience is required.
  • At least 3 years of hands-on Python experience for production data engineering.
  • At least 3 years of hands-on Databricks experience using Apache Spark, Delta Lake, notebooks or jobs in production, including working knowledge of Unity Catalog.
  • At least 3 years of experience with Microsoft Azure data and platform services such as Azure SQL, Azure Data Lake Storage, Key Vault, Azure Functions, Event Hubs, Azure Monitor, and Microsoft Entra ID.
  • Experience developing, supporting, and troubleshooting production on-premises SQL Server environments, including SSIS packages and SQL Agent jobs.
  • Demonstrated experience designing ETL/ELT pipelines, data warehouses or lakehouses, and dimensional data models.
  • Demonstrated experience implementing data quality, reconciliation, automated testing, operational monitoring, alerting, and production support practices.
  • Experience with Git-based development, peer review, CI/CD, automated deployments, and environment promotion using Azure DevOps, GitHub Actions, or comparable tooling.
  • Experience with Infrastructure as Code, such as Terraform or Bicep, to provision and manage data platform resources.
  • Experience designing and supporting workflow orchestration with Apache Airflow/Astronomer or a comparable enterprise orchestrator.
  • Experience mentoring engineers, leading technical design discussions, and influencing standards without formal supervisory authority.
  • Ability to write clear, maintainable, testable code and explain technical trade-offs to technical and non-technical audiences.
  • Ability to balance delivery speed with reliability, security, data quality, maintainability, and cost.
  • Ability to work independently on ambiguous problems while engaging appropriate partners before decisions create downstream risk.
  • Ability to communicate production risk, status, dependencies, and incidents directly and with appropriate urgency.
  • Ability to build effective working relationships across organizational levels and with external partners.
  • Ability to learn unfamiliar systems quickly and operate across modern cloud platforms and legacy environments during transition.
  • Ability to produce technical documentation, runbooks, diagrams, standards, and implementation guidance.
  • Ability to use AI tools responsibly, validate generated code, and protect sensitive data.

Responsibilities

  • Design, build, test, deploy, and support batch and near-real-time data pipelines using Databricks, Python/PySpark, Spark SQL, T-SQL, Azure services, and Apache Airflow/Astronomer.
  • Develop scalable lakehouse solutions using Delta Lake and medallion-style raw/bronze, refined/silver, and curated consumption layers.
  • Create and maintain dimensional, relational, and other fit-for-purpose data models for reporting, analytics, operational integrations, and AI/ML workloads.
  • Modernize legacy systems by assessing SQL Server, SSIS, SQL Agent, Informatica PowerCenter/IICS, and custom processes; defining migration patterns; and safely transitioning workloads to strategic platforms.
  • Develop, support, and tune on-premises SQL Server workloads, including databases, stored procedures, SSIS packages, and SQL Agent jobs, documenting systems and maintaining reliable operation during transition.
  • Build data quality controls for completeness, accuracy, reconciliation, freshness, schema conformance, and source-to-target parity; investigate discrepancies and drive them to root cause and resolution.
  • Engineer production workflows with idempotency, restartability, retries, backfills, dependency management, alerting, logging, auditability, and operational runbooks.
  • Apply software-engineering practices to data solutions, including Git-based source control, pull requests, peer review, branching standards, automated testing, CI/CD, environment promotion, and infrastructure as code.
  • Optimize pipeline performance and cost through incremental processing, efficient Spark and SQL design, right-sized compute, workload tuning, and reduced unnecessary full refreshes or data movement.
  • Partner with business stakeholders, Business Systems Analysts, application teams, architects, security, infrastructure, governance, analytics, and vendors to translate requirements into maintainable data solutions.
  • Design secure data access using Unity Catalog and Azure/Entra patterns, with least privilege, secrets management, lineage, sensitive-data handling, and separation of development, test, and production environments.
  • Integrate data from enterprise and third-party platforms, including APIs, files, SQL databases, Salesforce, and other operational systems, accounting for source-system changes and downstream impact.
  • Provide technical leadership through design reviews, code reviews, troubleshooting, standards development, reusable frameworks, mentoring, and constructive feedback to engineers at different experience levels.
  • Own production outcomes for assigned systems and data products, including incident response, root-cause analysis, corrective actions, documentation, and participation in a 24/7 on-call rotation.
  • Contribute to Agile delivery by refining work, estimating effort, communicating risk and dependencies, and delivering incremental value.

Desired Qualifications

  • Experience with Databricks Asset Bundles, Lakeflow or declarative pipeline patterns, Databricks SQL, and production administration or performance optimization.
  • Experience with data observability and quality frameworks such as DQX, Great Expectations, or comparable approaches.
  • Experience with Change Data Capture, Change Tracking, event-driven integration, streaming, and schema-evolution patterns.
  • Experience with legacy modernization involving Informatica PowerCenter/IICS, Windows Task Scheduler, or custom integration code.
  • Experience supporting governed consumption through Tableau, Excel/Power Query, Salesforce Data 360/Data Cloud, APIs, data sharing, or AI/ML workloads.
  • Familiarity with MLOps practices and operationalizing machine learning models, including deployment, monitoring, and supporting feature or training data pipelines.
  • Experience using AI-assisted and agentic development tools, such as GitHub Copilot or similar tools, to write, review, test, and troubleshoot code while validating AI-generated output.
  • Experience in financial services or another environment where security, auditability, data lineage, change control, and operational resilience are important.
  • Relevant certifications such as Databricks Certified Data Engineer Professional or Microsoft Certified: Azure Data Engineer Associate.

About the Company

GreatAmerica Financial Services

Provides equipment financing and leasing solutions

GreatAmerica provides equipment financing and leasing to manufacturers, vendors, and dealers, enabling end-user purchases across multiple industries. It works through channel partnerships and a technology platform for quoting, credit applications, and portfolio management, plus a Hardware-as-a-Rental option that lets customers offer an as-a-service model with no upfront financial risk. The company stands out as a private, family-owned, independent firm focusing on long-term partnerships, with specialized business units and advisory services. Its goal is to help channel partners grow sales and run sustainable businesses by offering flexible financing and value-added services.

Company size
1-10
Company stage
Debt Financing
Total funding
$1.5B
Headquarters
Cedar Rapids, IA
Founded
1992

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