AVP, Data Engineer
Location:
New York, NY / Chicago, IL
Experience:
8+ years
About the Role
We are looking for an experienced
AVP, Data Engineer
to design, build, and support modern data platforms and transformation pipelines. The role will focus on ingesting and transforming replicated source data into trusted, consumable data products for reporting, analytics, and downstream business users.
The ideal candidate will have strong expertise in
data modeling, SQL, Python, dbt, and data pipeline development
, along with experience working with modern analytical data platforms and workflow orchestration tools.
This is a
hybrid opportunity
, with the candidate expected to be within a commutable distance of the New York or Chicago office.
Key Responsibilities
Translate business requirements and data mapping documents into technical designs.
Develop and optimize SQL-based data transformations using
dbt
.
Build and maintain data pipelines using
Dagster
or similar orchestration tools.
Identify, troubleshoot, and resolve data quality and SQL-related issues.
Debug and troubleshoot issues identified during testing and production.
Monitor data pipelines and ensure reliable delivery of data products.
Communicate project status, technical issues, risks, and blockers effectively.
Identify opportunities for continuous improvement across data engineering processes.
Mentor junior engineers and contribute to technical best practices.
Participate in code reviews and promote quality engineering standards.
Required Qualifications
Bachelor's degree in Computer Science or a related field, or equivalent professional experience.
8+ years of Data Engineering experience
designing, developing, and supporting enterprise data platforms, ingestion frameworks, and transformation pipelines.
Strong hands-on expertise in:
SQL
Python
dbt
Experience developing and optimizing large-scale
ETL/ELT
solutions.
Hands-on experience with
Dagster, Airflow, or similar workflow orchestration tools
.
Experience building data ingestion and replication pipelines from:
PostgreSQL
Oracle
NoSQL sources
File-based data feeds
Experience working with
Snowflake, Databricks, or comparable modern data platforms
.
Strong understanding of data modeling concepts, including:
Dimensional Modeling
Medallion Architecture
Data Vault
Highly relational data structures
Experience transforming complex business data into reliable datasets for reporting, analytics, and downstream users.
Strong understanding of data engineering best practices, including:
Testing
Code reviews
Git/version control
CI/CD