Since Resonate's founding in 2008, the company has been driven by a simple but powerful idea: understanding people. Resonate empowers leading brands and agencies with deep consumer intelligence that ignites unbreakable relationships through better connections, more meaningful engagement and compelling customer experiences.
We are "people-centric." It is at the heart of what we do and drives how we operate. We reveal the Human Element—a holistic understanding of a person that starts with what makes us the most human—our values and motivations. In other words, we help you understand the "what" that drives the "why" people decide to choose, buy, endorse or abandon a brand or cause. By combining this human, person-based "why" with relevant data about your industry, brand or product, we help you create powerful marketing engagement that drives results.
As an engineering team member for the big data team, you will be responsible for the technical direction and development of critical data ingestion pipelines that power the Resonate business. You will be able to provide support and technical direction to a team of highly skilled data engineers and facilitate interaction with the technical product management team members. You will be a member of a high-quality, dedicated and friendly team passionate about delivering quality products, solving hard problems, and transforming the data and insights industry.
Responsibilities
- Collaborate in the design, planning and development of products and initiatives to deliver on product requests for the data engineering squad.
- Oversee production, quality assurance, quality control, testing and maintenance as required.
- Bachelor's degree in Computer Science, Computer Engineering, or equivalent.
- 7+ years professional experience in software engineering, data engineering, or a related field.
- 3+ years of experience in Spark/Scala DataFrame/Dataset APIs.
- Prior experience with debugging and problem solving in Big data ecosystem.
- Proven experience in tuning multi terabyte / petabyte scale Spark Applications.
- Prior relational database experience is required.
- Deep knowledge of software architecture and engineering standard methodologies, especially modern cloud computing stacks for processing Big Data.
- Experience with AWS as a cloud provider, Spark, Kafka, Hadoop, Elastic Stack, Java, Docker for containers, etc.
- Strong understanding of the different parts of the software development lifecycle, from exploration and design to delivery to production.
- Good understanding of principles of solution architecture, technical design, data structures, and data modeling.
- Prior experience with Non-functional requirements is required.
- Excellent communication skills.
- Positive attitude and excellent teamwork.
Preferred Qualifications
- Demonstrated success in implementing scaled high cardinality data system.
- Experience in using probabilistic data structures.
- Love for open-source technologies.
Benefits
Besides the opportunity to work with smart, fun, hard-working Resonate employees, you will have uncapped growth potential, a work/life balance, and a competitive suite of benefits.
Location
At Resonate, we're proud to offer a flexible work environment that combines the best of both worlds. Our team is made up of talented individuals who collaborate seamlessly across physical locations, thanks to our innovative hybrid and remote work policies. Whether you're working from home or from one of our state-of-the-art offices, you'll have access to the tools and resources you need to succeed.
Resonate is headquartered in Reston, VA with offices in New York City, and Washington, D.C. Be a part of the team that changes the industry!
Our EEO Statement:
Resonate is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
Find out more about our story at .
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