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Senior Data Engineer

2 months ago


Saint Petersburg, United States Kobie Full time
Job DescriptionJob Description

Why you will love working for a National Top Workplace

We are a global leader in loyalty marketing.

We work with some of the most well-known brands in the world to deliver market-leading, end-to-end loyalty solutions to enable customer experiences. With a strategy-led, technology-enabled approach, we are consistently named an industry leader by Forrester. The programs we deliver reach more than 330M consumers through loyalty. The impact of these loyalty programs affords us deep brand partnerships, owning a niche in the loyalty space where outcomes matter most.

We are a mission and values driven company.

Our mission is to grow enterprise value through loyalty for our clients. Every role within Kobie has a purpose and directly contributes to us achieving this mission.

We are values driven at every point. Over our 30+ year journey, we've created a fun, high-trust, transparent workplace. We believe in leadership and ownership. Our hybrid work environment, personal holidays, casual dress code and focus on diversity and inclusion add to a culture that makes our teammates proud. That pride shines through in the work we do for our clients.

About the team and what we'll build together

We find actionable insights in our clients' loyalty data that helps drive enterprise value. We create real time dashboards to inform internal and external stakeholders.

As a Senior Data Engineer at Kobie, you will play a vital role within our data engineering team, under the direct supervision of the Manager of Data Engineering. Your expertise will be instrumental in implementing ETL/ELT processes and data integrations, populating Kimball style star schemas from a diverse range of data sources across multiple data warehouse implementations in support of our product. Your involvement will extend from requirements gathering to designing business processes and dimensional models. Your profound comprehension of OLTP, Data Vault, and star schemas will be crucial as you delve into source data analysis to assess its potential in addressing business needs. Your objective will be to create scalable, efficient, auditable, and as much as possible, reusable processes.

How you will make an impact

  • Ensure seamless production support of daily running ETL/ELT processes.
  • Develop, design, optimize, and maintain ETL/ELT processes.
  • Conduct data profiling, and source to target mappings, capturing ETL and business metadata for populating Kimball style dimensional models.
  • Design automated tests and audit logging processes for every stage of our data pipelines.
  • Design, manage and build event-driven architectures to support real-time data flows and event processing.
  • Document ETL processes comprehensively including process flow diagrams.
  • Conduct functional and performance testing to identify bottlenecks and data quality issues.
  • Implement slowly changing dimensions as well as transaction, accumulating snapshot, and periodic snapshot fact tables.

What you need to be successful

  • At least 6 years of Data Engineering experience, with a minimum of 2 operating in Snowflake.
  • Deep understanding of Snowflake Data Platform (data sharing, data clean rooms, marketplace).
  • Understanding of Database Replication and how data flows from OLTP database systems, ELT architecture and design.
  • The ability to work independently across multiple projects, communicating effectively to internal data stakeholders across the organization.
  • The ability to integrate with a wide range of data sources, including APIs messaging systems to capture and normalize streaming data.
  • Possess the ability to design data pipelines from end to end and train other team members in best practices and processes.
  • Have a good grasp of the Software Development Life Cycle (SDLC) and Agile Development processes.
  • Deep understanding of Event Driven Architectures, how they impact Data Pipeline designs and integrations.
  • Cloud Experience with Azure or OCI, preferred.
  • Proficient in scripting languages such as Python, and JavaScript.
  • Experience with orchestration tools like Apache Airflow, Matillion, Mage.ai is preferred.
  • Data Replication tools experience like Kafka, Goldengate, HVR, Qlik Replicate, preferred.

Our teammates are at the heart of everything we do

Healthy people are happy people, which makes mental and physical health a top priority at Kobie. From robust health insurance and benefits options to free fitness programs like FitOn, to generous vacation time for yourself, we support your health needs fully. In today's job market, we know that employees are choosing only what works best for their life. For those that want career growth, Kobie is the perfect place. We have developed a comprehensive people strategy that helps every teammate know how to advance and progress on their career journey. Beyond title progression, Kobie's competitive pay, 401k matching, annual profit sharing and bonuses all make Kobie a perfect place to build your career.

Kobie a place for all

We don't just accept differences – we embrace, share, and celebrate them

Employment at Kobie is based solely on a person's merit and qualifications, directly related to professional competence. We do not discriminate against any teammate or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis under the law.

We are fiercely committed to fostering a workplace where teammates draw upon their own diverse backgrounds, experiences, and perspectives so that they feel welcomed to bring their authentic self to work every day. While our leadership team fully and completely supports our policy of nondiscrimination and equal opportunity, all teammates share the responsibility to ensure we incorporate the principles of equity, diversity, and inclusion throughout Kobie.


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