Freckle is the global leader in offline measurement and privacy compliant data. Freckle’s unique measurement solution supports all media verticals including mobile, desktop, social, radio, search, TV and out of home and is integrated into the worlds leading data and buying platforms including Salesforce, Google and others.
Freckle’s identity product Killi, a consumer-facing application was created to solve privacy and security challenges for consumers and compliance challenges for companies that purchase data around the world. By creating the world’s most compliant data set, Killi solves the privacy challenges that have recently been introduced in the EU (GDPR), the USA (CCPA), and CAN (PIPEDA).
At Freckle we are entrepreneurs and we are go-getters. We are a true startup. It is hard, but you will learn a lot. We work fast, have big aspirations and have a lot of fun along the way.
What you will be responsible for:
- Managing, coaching mentoring and expanding a small team of cross-functional data engineers. Currently, the majority of this team is offshore.
- Streamlining and improving the engineering processes, technologies and tools.
- Identifying and addressing gaps in the technical process to drive continuous delivery and improvement.
- Providing technical and architectural expertise, direction and decision to the team.
- Helping the product team achieve continuous and timely delivery, but knowing how to appropriately challenge timelines, client requests and other cross-functional deliverables.
- Being the final step in the solutioning and estimation process before the start of a new sprint.
- Auditing architecture/development plans and determine that scaling, reliability, operational needs match with business and client concerns.
- Aligning technical excellence with business goals.
What we need from you:
- 10+ years of building and leading engineering teams.
- 10+ years of experience in engineering or technical architecture.
- Experience with Spark, Hadoop, or other distributed processing technologies.
- Experience with NoSQL databases such as HBase, CassandraExperience in various programming languages and systems (mainly Scala and Python)
- Experience with creating big data pipelines on AWS/GCP/Azure (we use AWS and Databricks)
- Experience evaluating, procuring and using new technologies.
- Bachelors or Masters degree in Computer Science, Engineering or related discipline.
- Experience with Scrum/Agile/Kanban methodologies.
- You are a true leader – someone who enables and inspires their team to do their best work.
- You are the cornerstone for delivery, team management, culture and product quality for technology.
- You are intellectually curious and ask tough questions.
- You thrive in a fast-paced challenging environment.
- You are a proactive, driven, entrepreneurial and action-oriented individual who can accomplish goals.
- You enjoy staying ahead of the curve with a knowledge and interest in emerging technologies.
- You have a high energy and bring a positive attitude into everything you do.
What we would like to see as a bonus:
- An understanding of how Spark works.
- Experience in typed functional programming.
- Experience in building concurrent and reactive systems.
- Experience with deployment tooling such as Docker, Jenkins and Kubernetes.
- Experience leading and mentoring team members.
- Experience with Machine learning frameworks beyond linear regression.
- Experience in programmatic or digital advertising.
- Experience in real-time data processing.
- Experience with DataBricks.
What you will get from us:
- Competitive market compensation structure.
- Comprehensive, health, dental and vision plan.
- A great corporate culture.
- A fulfilling, challenging and flexible work experience.
- The opportunity for career growth.
- Wellness and professional development fund.
All interested candidates should apply through the following link: Director of Data Engineering
Freckle welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.