Data Engineer

AllianceBernstein L.P.; Nashville (TN); On-site; USD 90,000 - 115,000; Full time

Job summary

AllianceBernstein L.P. is looking for a Senior Associate in Data Engineering based in Nashville, TN. This role involves designing and maintaining scalable data pipelines, optimizing transformation models, and ensuring data quality.

The ideal candidate has 3+ years of experience in data engineering, is proficient in Snowflake, dbt, Fivetran, Python, and SQL, and thrives in a collaborative data-driven culture.

A Bachelor's degree in computer science is preferred, along with strong analytical skills and excellent communication abilities.

Qualifications

• 3+ years of experience in data engineering, data warehousing, or related fields.
• Excellent communication skills and a team-oriented mindset.
• Strong analytical skills with an ability to optimize queries and troubleshoot performance issues.

Responsibilities

• Design, build, and maintain scalable data pipelines using Fivetran and Snowflake.
• Develop and optimize dbt transformation models for analytics.
• Ensure data quality through robust testing and monitoring.
• Collaborate with data analysts and business teams to understand requirements.

Skills

Snowflake

dbt

Fivetran

Python

SQL

Data modeling techniques

Data governance frameworks

Airflow

Big data processing frameworks

Education

Bachelor's degree in computer science or related field

Job description

Who you’ll work with

We are seeking a Nashville, TN based Senior Associate, Data Engineering to join our dynamic Data Team. This role is ideal for a data engineer with experience in Snowflake, Fivetran, dbt, Python, and SQL who thrives on ingesting and transforming data from diverse sources, ensuring it is optimized for analytics and business intelligence. The ideal candidate is a hands‑on problem solver, eager to learn, and a strong team player who contributes to a collaborative data‑driven culture.

What you’ll do

• Design, build, and maintain scalable data pipelines to ingest and integrate data from multiple sources using Fivetran and Snowflake.
• Develop and optimize dbt transformation models to structure and prepare data for analytics and consumption.
• Ensure data quality, integrity, and reliability through robust testing, monitoring, and governance practices.
• Implement data modeling best practices in a data warehouse environment, optimizing for performance and usability.
• Work closely with data analysts, engineers, and business teams to understand data requirements and improve accessibility.
• Collaborate on improving internal data engineering processes, documentation, and best practices.

What we’re looking for

• 3+ years of experience in data engineering, data warehousing, or related fields.
• Proficiency in Snowflake, dbt, Fivetran, Python, and SQL for data transformation, automation, and pipeline development.
• Experience with data modeling techniques and best practices for modern cloud‑based data warehouses.
• Strong analytical skills with an ability to optimize queries and troubleshoot performance issues.
• Passion for continuous learning, innovation, and contributing to a strong data culture.
• Excellent communication skills and a team‑oriented mindset.
• Preferred: Bachelor’s degree in computer science or related field.
• Preferred: Experience with orchestration tools (e.g., Airflow) and data governance frameworks.
• Preferred: Familiarity with CI/CD for data pipelines and infrastructure‑as‑code principles.
• Preferred: Exposure to big data processing frameworks (e.g., Spark) is a plus.

Equal Opportunity Employer

AB does not discriminate against any employee or applicant for employment on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability, marital status, citizenship status, sexual orientation, gender identity, military or veteran status or any other basis that is prohibited by applicable law. AB’s policies and practices seek to ensure that employment opportunities are available to all employees and applicants based solely on job‑related criteria.