Principal Data Engineer

MeridianLink

177d • $148,000 - $202,000

About The Position

The Principal 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. The role will develop robust and scalable solutions that transform data into a useful format for analysis, enhance data flow, and enable end-users to consume and analyze data faster and easier.

Requirements

• 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.

Nice To Haves

• Previous experience democratizing data at scale for the enterprise.

Responsibilities

• Design, build, implement, and maintain data processing pipelines for ETL of data from various sources.
• Lead the writing of complex SQL queries to support analytics needs.
• Develop technical tools and programming that leverage AI, machine learning, and big-data techniques to cleanse, organize, and transform data.
• Maintain, defend, and update data structures and integrity on an automated basis.
• 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.
• Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, Databricks, Spark, Delta, APIs.
• Handle structured and unstructured data from data lakes, relational database management systems, and/or data warehouses.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree