Senior Data Engineer

Senior Data Engineer – Finance Data

Location

Remote – United States

Employment Type

Contract-to-Permanent

Salary

$125,000 - $160,000

Overview

GSD Search is partnering with a growing financial services organization to identify a Senior Data Engineer to support its Finance data domain.

This individual will play a key role in developing, maintaining, and enhancing the data pipelines, transformations, and warehousing solutions that support critical financial operations, reporting, and business decision-making.

We're looking for more than someone who can write great code. The ideal candidate is naturally curious, comfortable navigating ambiguity, and understands how data engineering supports broader business objectives. This person should be able to translate complex technical concepts into meaningful business outcomes while collaborating effectively with both technical and non-technical stakeholders.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes using Python, SQL, and modern data engineering technologies.
• Build and optimize data transformations and models using tools such as Coalesce or dbt.
• Develop and maintain data orchestration workflows using Airflow, Dagster, or comparable technologies.
• Work with cloud-based data warehousing platforms, preferably Snowflake, to support reliable and efficient data processing.
• Partner closely with Finance stakeholders to understand business requirements and translate them into effective data solutions.
• Ensure data accuracy, reliability, quality, and accessibility across financial datasets.
• Troubleshoot complex data pipeline issues, optimize performance, and continuously improve existing data engineering processes.
• Collaborate with data engineers, analysts, and business partners to support financial reporting, analytics, and operational initiatives.
• Communicate technical decisions, project progress, and business impact clearly to technical and non-technical audiences.
• Take ownership of engineering challenges, proactively identify opportunities for improvement, and operate effectively in an evolving environment.

Required Qualifications

• Strong professional experience in data engineering, including building and maintaining production-grade data pipelines.
• Advanced proficiency in Python for data processing, automation, and pipeline development.
• Advanced SQL skills, including complex queries, transformations, performance optimization, and data validation.
• Hands-on experience designing and implementing ETL/ELT processes.
• Experience with cloud-based data warehousing platforms such as Snowflake or Databricks.
• Experience with data transformation and modeling frameworks such as Coalesce or dbt.
• Experience with workflow orchestration tools such as Apache Airflow, Dagster, or similar technologies.
• Strong understanding of data warehousing concepts, dimensional modeling, and data architecture.
• Ability to work independently, navigate ambiguity, and solve complex problems without requiring highly prescriptive direction.
• Strong communication skills with the ability to explain technical solutions and their business value to diverse stakeholders.
• Business-oriented mindset with an understanding that successful data engineering is measured by the value delivered to the organization.

Preferred Qualifications

• Hands-on experience with Snowflake as a primary data warehousing platform.
• Experience supporting Finance, Accounting, Financial Reporting, or other financial services data domains.
• Experience building data solutions that support financial reporting, reconciliation, analytics, or operational decision-making.
• Familiarity with data governance, data quality frameworks, and performance optimization.
• Experience collaborating directly with Finance leaders, business analysts, and cross-functional technology teams.
• Demonstrated ability to identify business problems, ask thoughtful questions, and recommend practical technical solutions.

What Will Make You Successful

Technical expertise is important, but we're equally interested in how you approach problems and collaborate with others.

The strongest candidates will demonstrate

• Curiosity: You ask thoughtful questions, challenge assumptions, and seek to understand the bigger picture.
• Comfort with Ambiguity: You can move initiatives forward even when requirements aren't fully defined.
• Business Partnership: You understand the needs of Finance stakeholders and build solutions that deliver meaningful business value.
• Communication: You can explain complex technical concepts clearly and connect engineering decisions to business outcomes.
• Ownership: You take initiative, solve problems proactively, and follow through on commitments.

Keywords

Senior Data Engineer, Python, SQL, Snowflake, Databricks, ETL, ELT, Coalesce, dbt, Apache Airflow, Dagster, Data Warehousing, Data Modeling, Data Pipelines, Finance Data, Financial Services, Data Transformation, Data Orchestration.