Senior Data Engineer: Real-Time Data Platform Leader

MeridianLink, Inc.; United States; Sur place; USD 140 000 - 210 000; Plein temps

Résumé du poste

MeridianLink, Inc. is seeking a Senior Data Engineer to design, build, and maintain ETL pipelines from diverse data sources. You will lead complex SQL development to support analytics, while creating scalable data processes and robust data infrastructures.

In this role you will implement tooling that leverages AI/ML, big-data techniques, and automated data governance. Collaboration with engineering, data science, product, and compliance teams is essential to deliver reliable data models and

Qualifications

• Bachelor’s or Master’s degree in computer science, engineering, or related field.
• 6–8 years of experience in data engineering, with focus on financial SaaS platforms.
• Experience designing pipelines for ETL/ELT, data ingestion, transformation, and loading.

Responsabilités

• Design, build, implement, and maintain ETL data pipelines from diverse sources.
• Lead the writing of complex SQL queries to support analytics needs.
• Develop tools and code leveraging AI/ML and big-data techniques to cleanse and transform data.
• Evaluate tools and technologies for data infrastructure and processing; collaborate with multiple stakeholders to translate requirements into pipelines.
• Work with Python, SQL, Spark, Databricks, and data stores including data lakes, relational DBs, and data warehouses.

Connaissances

Analytical thinking

Stakeholder management

Problem solving

Data architecture

Security & automation

Continuous delivery

Formation

Bachelor’s or Master’s in CS/Engineering

Outils

Python

SQL

Apache Spark

Databricks

Snowflake

Redshift

BigQuery

Airflow

dbt

Description du poste

MeridianLink, Inc. is seeking a Senior Data Engineer to design, build, and maintain ETL pipelines from diverse data sources. You will lead complex SQL development to support analytics, while creating scalable data processes and robust data infrastructures.

In this role you will implement tooling that leverages AI/ML, big-data techniques, and automated data governance. Collaboration with engineering, data science, product, and compliance teams is essential to deliver reliable data models and