Data Engineer

Accelero; Columbus (OH); On-site; USD 95,000 - 140,000; Full time

Job summary

Accelero is establishing a Columbus office and is looking for a data engineer to join as one of the first engineers on the ground. You will design and implement data pipelines for banking and private capital clients, ensuring data is reliable and accessible for analysts and decision-makers.

You’ll collaborate with data scientists and consultants, bring in modern tooling, and tackle data engineering challenges across on-prem and cloud environments.

Qualifications

• 3–6 years as a data engineer or similar.
• Strong Python and SQL, with clean, performant code for large data volumes.
• Experience building data-intensive applications and pipelines, with an open mind on tooling.
• Familiarity with Spark, Databricks, Airflow, and cloud platforms (AWS/Azure/GCP).
• Modern engineering practices: version control, CI/CD, infrastructure as code.

Responsibilities

• Design and build data pipelines that pull from internal and external sources into client data platforms.
• Keep data reliable, available and high quality so clients can make better decisions.
• Work directly with data scientists, consultants and clients to make data easier to access and use.
• Bring in new tools and methods to improve how data is handled.

Skills

Python

SQL

Data pipelines

CI/CD

Infrastructure as code

Data quality

Education

CS or quantitative degree

Tools

Spark

Databricks

Airflow

AWS

Azure or GCP

Job description

Be one of the first engineers in a brand-new Columbus office, building data platforms for banking and private capital clients.

My client is a fast-growing technology consultancy backed by major names in global consulting and finance. In just a couple of years they’ve grown to offices across three continents, delivering data, AI and software solutions to clients in complex, high-stakes environments.

They’re building a team here from the ground up, with dozens of positions opening over the next few years. Join now and you’ll help shape how the team works, what it builds and who joins next.

You’ll sit close to clients, solve problems tied to financial markets and world events, and work alongside data scientists, AI engineers and quants who are among the best in their fields.

Before you apply

• US citizens only. Visa sponsorship is not available.
• Degree in Computer Science or a quantitative field from a top-ranked university, with a minimum 3.3 GPA.

What you’ll do

• Design and build data pipelines that pull from internal and external sources into client data platforms
• Keep data reliable, available and high quality so clients can make better decisions
• Work directly with data scientists, consultants and clients to make data easier to access and use
• Bring in new tools and methods to improve how data is handled

What you'll bring

• 3 to 6 years as a data engineer or similar
• Strong Python and SQL, with clean, performant code for large data volumes
• Experience building data-intensive applications and pipelines, with an open mind on tooling
• Some or all of: Spark, Databricks, Airflow, AWS, Azure or GCP
• Modern engineering practices: version control, CI/CD, infrastructure as code
• A track record of testing, troubleshooting and improving data quality
• Financial services, risk management or consulting experience (a plus)