Senior Data Engineer

MeridianLink

. Design, build, implement, and maintain data processing pipelines for ETL from varied data sources .

Posted 10/14/2026full-timeRemote • United StatesSenior💰 $95,000 - $135,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing data processing pipelines, leveraging Python, SQL, and distributed processing frameworks to support financial systems. Strong focus on data governance, security, and compliance within financial services, with experience in cloud-based data platforms.

Highest-signal resume keywords

Data EngineeringPython ProgrammingSQL Query WritingApache SparkData Governance

ATS Keywords

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Hard Skills

Data Processing PipelinesETLMachine LearningBig Data TechniquesData StructuresData OrchestrationData WarehousingData ModelingData SecurityAnalytical Problem-Solving

Soft Skills

CollaborationPersuasionIndependent Judgment

Tools & Technologies

DatabricksSnowflakeRedshiftBigQueryAirflowDbtAWSAzureAPIsData Lakes

Industry Keywords

Financial SystemsSaaS PlatformsData ComplianceStructured DataSemi-Structured Data

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudETLPythonSparkSQL

About the role

Key responsibilities & impact

Design, build, implement, and maintain data processing pipelines for ETL from varied data sources
Lead the writing of complex SQL queries to support analytics needs
Develop technical tools and programs leveraging artificial intelligence, 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 stakeholders to translate business requirements into technical specifications and coded data pipelines
Architect and scale a modern data platform supporting real-time and batch processing for financial forecasting, risk analytics, and customer insights
Enforce standards for data governance, quality, lineage, and compliance
Partner with engineering, finance, sales, and compliance stakeholders to create reliable data models and workflows
Evaluate emerging technologies and lead proofs of concept shaping the data stack
Champion security, automation, and continuous delivery in data workflows
Work with R, Python, SQL, Databricks, Spark, Delta, APIs, data lakes, relational database management systems, and data warehouses

Requirements

What you’ll need

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 such as Airflow or dbt
Experience with data warehouses such as Databricks, Snowflake, Redshift, or BigQuery
Strong understanding of data security, privacy, and compliance within a financial services context
Experience working with structured and semi-structured data such as Delta, JSON, Parquet, and Avro at scale
Familiarity with modelling datasets in Salesforce, Netsuite, and Anaplan required
Ability to assess unusual circumstances and use sophisticated analytical and problem-solving techniques
Ability to work independently through independent judgment
Ability to enhance relationships and networks with senior internal partners, often requiring persuasion
Previous experience democratizing data at scale for the enterprise is a plus

Benefits

Comp & perks

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