Join our dynamic Data Engineering team and drive improvements in the reliability and observability of critical data pipelines. This role offers the chance to make a significant impact within an organization that prioritizes data. We are a focused team with ambitious goals, seeking passionate individuals adept at tackling complex challenges at scale. You'll be instrumental in supporting and building distributed systems in a fast-paced, collaborative setting. On-call and weekend rotations are part of the role, balanced with a commitment to work-life harmony.

As an Incident Commander, you'll assist with on-call duties, categorizing and tracking real-time data incidents, and coordinating engineering resources for swift resolution. You will champion the problem management process, ensuring thorough root cause analysis of data incidents and prioritizing follow-up actions with partner teams. A key contribution will be to our long-term Incident and Problem Management strategy, helping develop a Data Reliability Observability Platform to quantify incident impacts, automate issue detection, and monitor data and pipeline health. Collaborate with support and data quality teams to define success KPIs, ensure observability and automation coverage, and create insightful dashboards and visualizations.

We require a Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent work experience. A minimum of 3 years of relevant data engineering experience is essential. Candidates should possess a strong understanding of data modeling principles, including Dimensional modeling and data normalization. Experience with process engineering and continuous improvement is crucial, alongside a detailed problem-solving approach and a proactive sense of ownership. Excellent written and verbal communication skills, with experience in presentations, are necessary. Comfort in a fast-paced, highly collaborative environment and familiarity with Agile Scrum principles are expected. Preferred qualifications include 2+ years of experience with analytic SQL, traditional relational databases, and/or distributed systems like Snowflake or Redshift, along with experience in programming languages such as Python or Pyspark.