Senior Data Engineer

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October 22

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MeridianLink

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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.

501 - 1000 employees

Founded 1998

💳 Fintech

🏦 Banking

☁️ SaaS

💰 $485M Post-IPO Debt on 2021-11

📋 Description

• The Senior Data Engineer will design, build, implement, and maintain data processing pipelines for the extraction, transformation, and loading (ETL) of data from a variety of data sources. • Expected to lead the writing of complex SQL queries to support analytics needs. • Responsible for developing technical tools and programming that leverage artificial intelligence, machine learning, and big-data techniques to cleanse, organize and transform data and to maintain, defend and update data structures and integrity on an automated basis. • Senior Data Engineers will evaluate and recommend tools and technologies for data infrastructure and processing. Collaborate with engineers, data scientists, data analysts, product teams, and other stakeholders to translate business requirements to technical specifications and coded data pipelines. • The role will work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, Databricks, Spark, Delta, APIs. Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses.

🎯 Requirements

• Bachelor's or master's degree in computer science, Engineering, or a related field. • 6-8 years of experience in data engineering, with a strong focus on financial systems on SaaS platforms. • Deep expertise in Python, SQL, and distributed processing frameworks like Apache Spark, Databricks, Snowflake, Redshift, BigQuery. • Proven experience with cloud-based data platforms (preferably AWS or Azure). • Hands-on experience with data orchestration tools (e.g., Airflow, dbt) and data warehouses (e.g., Databricks, Snowflake, Redshift, BigQuery). • Strong understanding of data security, privacy, and compliance within a financial services context. • Experience working with structured and semi-structured data (e.g., Delta, JSON, Parquet, Avro) at scale. • Familiarity with modelling datasets in Salesforce, Netsuite and Anaplan to solve business use cases required. • Previous experience Democratizing data at scale for the enterprise a huge plus.

🏖️ Benefits

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