Senior Data Engineer

Franklin Fitch; Atlanta (GA); Remote; USD 165,000 - 200,000; Full time

Benefits offered by this job

Fully remote

Base salary $165,000–$200,000

Bonus

Job summary

Franklin Fitch is hiring a Data Engineer for a fully remote role based in the Atlanta Metropolitan Area. You will design and operate batch and streaming data pipelines on a cloud-native platform, handling high-volume data across financial services workflows.

You will own data quality, governance and platform reliability while collaborating with Analysts, ML engineers and product teams. The role offers substantial growth as the data stack is rebuilt with modern tooling and scalable architectures.

Qualifications

• 5+ years in data engineering.
• Strong SQL and Python.
• Experience with cloud platforms (AWS/Azure/GCP) and orchestration tools.

Responsibilities

• Batch and streaming pipelines at scale on a cloud-native platform.
• Data quality, lineage and governance for reliable numbers.
• Platform performance and cost improvements.

Skills

Senior data engineer

SQL

Python

Cloud platforms

Airflow/Dagster

Tools

Airflow

Dagster

Snowflake

Databricks

dbt

Job description

Full-time | Remote | $165,000 to $200,000 base + bonus | Atlanta, GA

This is a fully remote opportunity, but applicants need to be based in the Atlanta Metropolitan Area.

What happens when data engineering sits at the centre of the business? Data that moves money, informs risk and supports decisions in real time, built by a team trusted to get it right.

We're partnering with a financial services technology business rebuilding its data stack from the ground up. Streaming and batch at serious volume, a cloud-native platform, and leadership who see data as a core strategic asset and invest accordingly. Data engineers here are valued partners in how the business operates. Remote, and technically rich enough to keep growing in.

Key Responsibilities

What you'll build

• Batch and streaming pipelines at scale on a modern cloud-native platform
• Data foundations that power analytics, machine learning and AI use cases
• Reusable frameworks that let other teams self-serve with confidence

What you'll own

• Data quality, lineage and governance, so people can rely on every number
• Platform performance and cost, with room to improve what needs improving
• Reliability of the pipelines the business depends on every day

What you'll influence

• Architecture and tooling choices across the data function
• How analysts, ML engineers and product teams work with data
• The standards and practices future engineers will build on

Key Skills & Qualifications

Required

• 5+ years in data engineering
• Strong SQL and Python
• Cloud experience (AWS, Azure or GCP) and orchestration tools such as Airflow or Dagster
• A thoughtful approach to designing for scale, failure and change

Preferred

• Kafka or other streaming technologies
• Snowflake or Databricks, plus dbt
• Financial services or other regulated environment experience

What's on offer

• Fully remote, with a base of $165,000 to $200,000 plus bonus
• A large-scale rebuild with real investment behind it
• Work where data quality has visible, measurable impact