Data Engineer

🕒 June 22

🇺🇸 United States – Remote

💵 $95k - $140k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🚰 Data Engineer

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MeridianLink

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1998

💳 Fintech

🏦 Banking

☁️ SaaS

💰 $485M Post-IPO Debt on 2021-11

Fintech • Banking • SaaS

MeridianLink is a leading provider of SaaS solutions for financial institutions, specializing in loan origination systems and digital transformation technologies. Their end-to-end platform enhances digital experiences through integration with mortgage LOS, deposit account opening solutions, and more. MeridianLink's cloud-based systems improve efficiency in loan processing and collections, data-driven decision-making, and account management. The company collaborates with partners to expand market reach and drive growth in the fintech industry. With over 25 years of experience, MeridianLink is dedicated to supporting banks, credit unions, and other financial service providers through technology and business intelligence.

📋 Description

• Design, develop, and maintain scalable data pipelines and data products for internal and external consumers. • Build and optimize batch and near real-time data ingestion, transformation, and delivery processes. • Integrate data from internal and external sources to support business, reporting, and analytics requirements. • Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions and support Sisense dashboards and analytics assets. • Design and implement data models that support reporting, analytics, and operational use cases. • Ensure data quality, reliability, and performance through monitoring, validation, automated testing, and troubleshooting. • Write maintainable, well-documented, and testable code; participate in code reviews; and leverage AI-assisted development tools to improve quality and efficiency. • Support CI/CD, infrastructure automation, technical documentation, and continuous improvements to data architecture, tooling, and engineering practices

🎯 Requirements

• 2–4 years of professional experience in Data Engineering, Data Warehousing, or related roles. • Strong hands-on experience with Python and SQL for building scalable data pipelines and transformation logic. • Experience with Apache Spark, Parquet, and Azure Databricks, including Databricks workflows, Delta Lake, Delta Sharing, and Unity Catalog. • Strong SQL expertise including performance tuning, indexing, partitioning, query optimization, and stored procedure development. • Solid understanding of ETL/ELT methodologies, data warehousing principles, and modern data engineering best practices. • Experience designing and implementing data models to support analytics, reporting, and operational use cases. • Experience supporting or working with BI tools such as Sisense (or similar platforms). • Experience with CI/CD pipelines and version control practices (e.g., GitLab, Jenkins, or equivalent). • Experience working in fast-paced product environments with an emphasis on delivery, maintainability, and minimizing technical debt. • Strong communication skills with the ability to collaborate across technical and non-technical stakeholders

🏖️ Benefits

• Insurance coverage (medical, dental, vision, life, and disability) • Flexible paid time off • Paid holidays • 401(k) plan with company match • Remote work