Job Brief

At Twelve, Data Engineering is pivotal in building efficiencies and insights at scale that drive decisions to optimize end to end procurement, product manufacturing, sales, and distribution. Twelve is focused on transforming CO2 emissions into high value products and thereby making carbon reuse at scale economically viable. Our growing list of customers includes Alaska Airlines, Shopify, Procter & Gamble, US Air Force, NASA, and Mercedes. This role reports to the Senior Data Architect role and is part of the Information Technology team.

The core objectives of this role are to write robust data pipelines that collect, clean, and map data from various applications into the central data warehouse. This role partners with data architects, data analysts and engineers from various parts of the organization. This foundational role grows into solving unique use cases that will influence the direction of data engineering within Twelve. 

What you will do

• Own the data engineering design, pipelines, tests and codebase
• Own the monitoring, alerting, documentation, and on-call runbooks
• Write and maintain data mappings and transformations from various application APIs
• Write and maintain data aggregates using SQL or Spark based solutions
• Solve query performance, data latency and data quality issues at scale
• Share data engineering brown bags once a quarter on big impact initiatives
• Own the twelve data engineering blog

Who you are

• Experience in reliable batch data processing
• Experience in solving a subset of issues related with idempotency, data distribution, data latency, data lag and data replay
• Experience with monitoring data quality and data integrity and healing data through automated replay
• Fluent in writing efficient SQL (using data pruning concepts)
• Fluent in coding best practices
• Fluent in Python 3’s PySpark, NumPy, Dask (handing dataframes)
• Working knowledge of Airflow and/or DBT framework
• Experience in Data modeling in OLTP (3NF), OLAP (SCD, Star Schema) and representing nested structures in database clusters
• Have experience in working with Big Data batch processing (Airflow, Spark, parquet file type, Snowflake, BigQuery) 
• Have data integration experience using third party APIs in Python
• Willing to push the envelope in designing and implementing scalable data pipelines
• Love to optimize data processing for compute and storage resource efficiencies and performance for internal customers
• Care about data quality and data integrity
• Two years of batch data processing experience at scale

Twelve Benefits

• Medical, dental, and vision coverage
• Paid sick days and vacation
• Competitive salary and equity compensation commensurate with experience
• Diverse and inclusive work environment

Job Summary