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Salary: USD 88,525 - 0 / annual
Adelaide is a fast-growing measurement company specializing in attention measurement and activation for advertising. Since 2020, the company has become the trusted media quality measurement partner for 40% of Fortune 50 brands, with an award-winning AU metric that helps brands plan smarter campaigns and invest in high-quality inventory. The company has grown from 9 people in 2019 to over 75 employees and continues to scale rapidly with a 35% three-year CAGR.
You will lead Adelaide's data engineering team as a hands-on Lead Data Engineer, reporting to the Director of Engineering, DevOps & Data Engineering. This role supervises one Data Engineer and is responsible for the design, reliability, and performance of Adelaide's data pipelines and data infrastructure. You'll work with a team of data engineers and data scientists to structure and maintain the network of data flowing from internal and external sources into the company's SaaS analytics dashboard and connected platforms.
Key responsibilities include:
- Structure a sophisticated network and pipeline of data across internal and external sources
- Maintain high uptime for the SaaS analytics dashboard and connected platforms
- Design, build, deploy, and maintain reliable data pipelines with other team members
- Maintain and optimize existing data pipelines and integrations
- Optimize data stores for fast, efficient querying to support technology and reporting needs
- Ensure quality, reliability, and security of data infrastructure
Adealaide operates as a remote-friendly company with flexible work options, with offices in New York and London. The culture emphasizes action-oriented work, curiosity, rigor, and belonging. The company offers continuous learning opportunities, access to a network of prominent investors and advisors, mentorship from adtech and media executives, internal knowledge-sharing sessions, and an education budget for professional development.
Benefits include medical, dental, and vision insurance; paid time off; parental leave; employee development and wellness stipend; holiday break; volunteer time off; competitive salary; performance-based quarterly bonus; stock options; and 401(k) retirement plan.
Requirements:
- Bachelor's degree in Computer Science
- Proficiency in Python, Redshift, Postgres, SQL, Spark, Scala, and Airflow
- Experience with Pandas library and Docker
- Familiarity with AWS technologies (ECS, S3, Kinesis, Redshift, EMR)
- Strong understanding of data structures and algorithms
- Experience with machine learning
- Passion for delivering high-quality, reliable data solutions
Optional qualifications that set candidates apart:
- Experience in ad tech, measurement, or verification
- Experience with high-throughput or near-real-time data pipelines
- Experience with Snowflake or Looker
