Join our dynamic team as a Lead Associate in Data Engineering, focusing on enhancing the reliability and observability of critical data pipelines. You'll be instrumental in an organization that prioritizes data excellence. We're seeking passionate individuals ready to tackle complex challenges at scale within a fast-paced, collaborative environment. This role involves contributing to distributed systems and requires participation in on-call and weekend shifts on a rotational basis, balanced with a commitment to work-life harmony.

As an Incident Commander, you will assist in managing real-time data incidents, coordinating engineering resources for prompt resolution. You will also drive the problem management process, ensuring root cause analysis and prioritization of follow-up actions. Your contributions will shape our long-term Incident and Problem Management strategy through the development of a Data Reliability Observability Platform.

Key duties include quantifying incident impacts, automating issue detection, and tracking data and pipeline health. You'll collaborate with support and data quality teams to define success KPIs, ensure pipeline observability and automation, and build dashboards for monitoring overall data health.

We are looking for candidates with at least 3 years of hands-on data engineering experience. A strong grasp of data modeling principles, including Dimensional modeling and data normalization, is essential. Experience in process engineering and continuous improvement, coupled with a detailed problem-solving approach and a strong sense of ownership, is highly valued.

Excellent written and verbal communication skills are required, as is comfort in a fast-paced, highly collaborative setting. Familiarity with Agile Scrum principles and ceremonies is expected. Preferred qualifications include 2+ years of experience in implementing and reporting on business KPIs in data warehousing, exposure to reliability engineering best practices, and experience with analytic SQL and relational/distributed systems like Snowflake or Redshift.

Additional preferred experience includes 1+ year in programming languages such as Python or Pyspark, and familiarity with tools like Snowflake, Databricks, EMR, Spark, and Airflow. A Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent work experience, is required.