Data Engineer

athvin; United States; Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Remote work in the US

Full-time employment

Job summary

athvin is seeking a data engineer to build and own data pipelines that ingest ticketing, CRM, email, and donation data. You will model and transform data using SQL, ensure data quality, and enable observability across a columnar stack including Parquet and DuckDB.

You will work with an emphasis on reliable pipelines, identity resolution, and scalable data warehousing concepts. This role is remote within the United States and is full-time.

Qualifications

• Strong SQL and data modeling fundamentals.
• Hands-on experience building ETL workflows or data pipelines.
• Careful approach to data quality.
• Familiarity with columnar formats such as Parquet and with data warehouse concepts.

Responsibilities

• Design and own ETL pipelines that ingest ticketing, CRM, email, and donation data.
• Model and transform data with SQL and a SQL-based transformation framework.
• Establish data quality checks, testing, and observability throughout the pipeline.
• Work with Parquet, object storage, and DuckDB in a columnar, in-memory environment.
• Help reconcile source records into unified fan records.

Skills

SQL

Data modeling

ETL pipelines

Data quality

Tools

DuckDB

Parquet

Object storage

Job description

Role overview

Build data pipelines that bring information from disconnected source systems into clean, unified fan records. The role covers ingestion, transformation, modeling, and data quality across a columnar data stack, with ownership of pipeline reliability and visibility.

Responsibilities

• - Design and own ETL pipelines that ingest ticketing, CRM, email, and donation data.
• - Model and transform data with SQL and a SQL-based transformation framework.
• - Establish data quality checks, testing, and observability throughout the pipeline.
• - Work with Parquet, object storage, and DuckDB in a columnar, in-memory environment.
• - Help reconcile source records into unified fan records.

Requirements

• - Strong SQL and data modeling fundamentals.
• - Hands-on experience building ETL workflows or data pipelines.
• - Careful approach to data quality.
• - Familiarity with columnar formats such as Parquet and with data warehouse concepts.

Nice to have

• - Python or Rust experience.
• - Interest in identity resolution.

Benefits and work setup

• - Full-time, remote role based in the US.