Staff Data Engineer

In this role, you’ll leverage your past experiences and deep understanding of data warehousing and data lake concepts to help shape and execute Affinity's roadmap. You’ll champion engineering best practices, delivery velocity, and act as a technical mentor for other engineers on the team. You’ll play a significant role in defining the future of how businesses around the world use their relationships.

Design scalable and reliable data pipelines to consume, integrate and analyze large volumes of complex data from different sources to support the growing needs of our business.
Help define our data roadmap. You'll collaborate with our team of data engineers, machine learning engineers, product, and business leaders to help to answer these questions and more.
Build frameworks for measuring and monitoring data quality and integrity.
Establish CI/CD processes, test frameworks, and infrastructure-as-code tooling.
Implement, and build data solutions using Spark, Python, Databricks, and the AWS ecosystem (S3, Redshift, EMR, Athena, Glue).
Mentor, coach, and inspire the engineers on the team.
Identify and fill gaps in the team, and create the processes necessary for the teams’ success.

You have 8+ years of experience working in data engineering, with at least 3+ years of acting as a senior team lead or staff engineer, leading complex, sometimes ambiguous engineering projects across team boundaries.
You have extensive hands-on experience in building scalable data platforms and reliable data pipelines using technologies such as Spark, Hadoop, Databricks, AWS SQS, AWS Kinesis, and/or Kafka.
You have experience working with large, multi-terabyte datasets and are comfortable with high-scale data ingestion, transformation, and distributed processing tools such as Apache Spark (Scala or Python).
Experience with AWS, DBX or related cloud technologies.
You're comfortable with the building blocks of modern back-end systems, such as horizontally scalable data infrastructure, event-driven architecture, and beyond and can clearly articulate the pros/cons of different approaches, while also providing a recommended solution based on the current context.
You have familiarity with databases and analytics technologies in the industry, including Data Warehousing, Data Lakes, ETL and Relational Databases.
You have experience mentoring and helping the engineers around you grow.
​​You have experience partnering with product and machine learning teams on large, strategic data projects and routine partner work.
You take pride in delivering exceptionally high quality work in terms of data accuracy, performance, and reliability.