About Cardlytics 

At Cardlytics (NASDAQ: CDLX), we created an industry…. but we are just getting started. From idea inception at a kitchen table in Atlanta to now publicly traded on NASDAQ with offices around the world, we are proud of the work we’ve accomplished and are looking for more smart and creative minds to join us on our mission.

By using data for good, we connect brands with real people through their banks’ digital channels (think: online and mobile apps). And when we make these connections, everyone wins - brands drive more sales, banks drive more loyalty, and people receive more cash back. It’s that simple.

So how exactly does it work?

Through our partnerships with financial services companies like Chase, Bank of America, Wells Fargo, and Venmo, we have insights into one out of every two card swipes in the U.S. This equates to roughly $3.1 trillion in annual purchase spend from more than 161 millionbank customers.

Respecting this complete view of the consumer, we can create mutually beneficial relationships between those consumers and their favorite brands and financial services partners. These are relationships that otherwise would not have happened without our help. It’s our advanced targeting that drives advertising performance - because performance matters, and it’s our superpower.

Are you ready to become a shareholder and join a team filled with creatives and data scientists, consultants and artists, to help redefine marketing?

As a Data Engineer, you will:

• Develop new applications and features within a scrum team providing data and data services to the enterprise, other engineering teams, data science, analysts, product, management/executives, and other business teams
• Build high performing and scalable data platforms to support multiple data pipelines to ingest and deliver data as fast and reliably as possible
• Implement new technologies and practices to provide the best solutions to our customers
• Be responsible for architecture/design and risk analysis/mitigation on a micro and feature level
• Develop and maintain solutions on our tech stack environments (Spark Structured Streaming, Spark, Kafka, Traditional RBDMS, MPP RBDMS, etc.)
• Work with business teams to understand requirements and deliver within time and scope
• Work with IT Operations and Prod Support to ensure solutions are releasable, maintainable, and scalable
• Work with Risk & Compliance to ensure necessary logging/security is in place to comply with audits
• Help team members through code reviews, enforcing standards, best practices, policies, and processes
• Perform functional testing, end-to-end testing, performance testing, and UAT of applications and code written by self and other members of the team
• Participate in POCs as requested for new related tech versions, toolsets, and solutions both built and bought to prove viability for given business cases

You have:

• 4 years of data engineering and/or modern data warehousing experiences in Spark Streaming, Spark, Kafka, RDBMS in Scala/Java and SQL.

• 1 years of diagnosing issues and tuning applications in various environments
• Knowledge of serialization technologies: Avro
• Experience with AWS or other cloud vendors
• Proficient knowledge of optimization, concurrency, scale-up vs scale-out, encryption, application- and process-level security, etc. in an Apache/Hadoop environment is a plus
• Excellent verbal and written communication skills required
• Bachelor’s degree in Computer Science, MIS or related field or equivalent relevant experience
• Big pluses: Functional Programming, Columnar Storage Format (e.g. Parquet), Data Lake Architecture/Implementation, Git-like source control, Test Driven Development, Fintech/Adtech Experience

You are:

• Able to express yourself and articulate your ideas clearly, thoroughly, and respectfully; you listen the same way, and you do both across all levels of the organization with confidence
• Able to offer opinions and make decisions with limited information; able to accept and manage risk and drive change
• Able to take abstract ideas, formulate an actionable strategy, and execute on time and on scope
• A self-starter: you drive projects forward with limited oversight
• Passionate: you have genuine interest and enthusiasm about data, data technologies, and solving data challenges