MeridianLink develops cloud-based software for banks, credit unions, and other financial service providers. Its SaaS platform supports loan origination and processing, collections, mortgage lending, deposit account opening, and account management, with tools for digital customer experiences and data-informed decisions. Founded in 1998, the company works across fintech, banking, and SaaS, and partners with organizations to extend its reach. Its teams build technology and business intelligence products for financial institutions.
Senior Data Engineer at MeridianLink (Remote, US)
Build scalable ETL and analytics platforms for MeridianLink, a financial services software provider. Develop secure data pipelines for forecasting, risk analysis, and customer insights.
विवरण
- Build and maintain ETL pipelines that process data from varied sources.
- Write complex SQL queries to meet analytics needs.
- Create tools using AI, machine learning, and big data techniques to clean, organize, and transform data.
- Automate the maintenance and protection of data structures and integrity.
- Assess and recommend tools and technologies for data infrastructure and processing.
- Work with engineering, data science, analytics, product, and stakeholder teams to turn business needs into technical specifications and data pipelines.
- Design and scale a modern data platform for real-time and batch processing that supports financial forecasting, risk analysis, and customer insights.
- Apply standards for data governance, quality, lineage, and compliance.
- Partner with engineering, finance, sales, and compliance teams to build dependable data models and workflows.
- Assess emerging technologies and lead proofs of concept to shape the data stack.
- Promote security, automation, and continuous delivery across data workflows.
- Use R, Python, SQL, Databricks, Spark, Delta, APIs, data lakes, relational databases, and data warehouses.
आवश्यकताएँ
- Bachelor’s or master’s degree in computer science, engineering, or a related discipline.
- Six to eight years of data engineering experience, with a strong focus on financial systems on SaaS platforms.
- Advanced knowledge of Python, SQL, and distributed processing frameworks such as Apache Spark, Databricks, Snowflake, Redshift, or BigQuery.
- Experience with cloud data platforms, preferably AWS or Azure.
- Practical experience with orchestration tools such as Airflow or dbt.
- Experience with data warehouses such as Databricks, Snowflake, Redshift, or BigQuery.
- Strong understanding of data security, privacy, and compliance in financial services.
- Experience processing structured and semi-structured formats such as Delta, JSON, Parquet, and Avro at scale.
- Familiarity with modeling datasets in Salesforce, NetSuite, and Anaplan is required.
- Able to assess unusual situations and apply advanced analytical and problem-solving skills.
- Able to work independently and exercise sound judgment.
- Able to build relationships and networks with senior internal partners, including through persuasion.
- Experience making data broadly accessible across an enterprise is a plus.
लाभ
- Medical, dental, vision, life, and disability insurance coverage.
- Flexible paid time off.
- Paid holidays.
- 401(k) plan with company matching.
- Remote work.