Senior Data Engineer – Hybrid, Spark & Flink

Sprouts Farmers Market; Phoenix (AZ); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Competitive pay

Sick time plan

Vacation accrual plan

Opportunities for career growth

15% discount for you and one other in-

Flexible schedules

Employee Assistance Program (EAP)

401(K) Retirement savings plan with a

Company paid life insurance

Contests and appreciation events

Job summary

Sprouts Farmers Market is seeking a data engineer to own design, delivery, and operation of data domains and pipelines in a hybrid Phoenix environment. You will tackle complex data problems, build batch/streaming pipelines, and ensure data quality and observability across products.

The role requires at least 5 years of data engineering experience and hands-on work with Spark, Flink, Airflow, dbt, Kafka, and lakehouse formats. Collaboration and mentoring are encouraged as the team grows.

Qualifications

• 5+ years of data engineering experience.
• Experience with Spark, Flink, Airflow, dbt, Kafka, lakehouse formats, data quality, and observability.

Responsibilities

• Own the design, delivery, operation, and continuous improvement of assigned data domains, pipelines, and data products.
• Conduct detailed analysis to resolve difficult data engineering problems involving related systems or disciplines.
• Build batch and streaming pipelines and implement stable data contracts, quality controls, lineage, and observability.
• Explain technical designs to engineering and data consumers and ensure shared understanding.
• Provide technical guidance and training to associate and intermediate engineers; may delegate work and review work products.
• Operate assigned data products independently and seek leadership guidance for broader architectural or governance decisions.

Skills

Data engineering

Spark

Flink

Airflow

dbt

Kafka

Observability

Data quality

Job description

Sprouts Farmers Market is seeking a data engineer to own design, delivery, and operation of data domains and pipelines in a hybrid Phoenix environment. You will tackle complex data problems, build batch/streaming pipelines, and ensure data quality and observability across products.

The role requires at least 5 years of data engineering experience and hands-on work with Spark, Flink, Airflow, dbt, Kafka, and lakehouse formats. Collaboration and mentoring are encouraged as the team grows.