Senior Data Engineer

Salary: $126,000 - 166,000 per year Requirements:

• We require 4+ years of software development experience.
• We expect strong understanding of application design patterns, event-driven architecture, databases, schemas, and testing strategies.
• We require solid knowledge of continuous integration, continuous deployment, and test-driven development.
• A bachelors degree or equivalent experience in MIS, Computer Science, or a related field is preferred.
• Experience with large-scale application troubleshooting and performance tuning is preferred.
• Exposure to major cloud platforms such as Google Cloud Platform, AWS, or Azure is preferred.
• Familiarity with extreme programming practices is preferred.

• We develop high-quality applications that are robust, observable, and measurable using extreme programming practices and a user-focused approach.
• We participate in the full application lifecycle alongside designers, product managers, and engineers.
• We use critical thinking, experimentation, data, and industry best practices to drive business outcomes.
• We facilitate group discussions and team ceremonies to build shared understanding.
• We give and receive feedback in a way that is empathetic, actionable, and specific.
• We practice emergent architecture with sensible defaults and build software that is easy to use and modify.
• We define and lead product engineering and software standards.
• We shape new products from the user perspective by exploring problem spaces and ranking feasible solutions to test.
• We research technology market trends and emerging practices.
• We lead technical initiatives across the team and broader department.
• We may take on additional duties as needed.
• We develop, automate, and maintain batch and streaming ETL pipelines using Apache Airflow, Apache Spark, Python, and Scala.
• We build and manage cloud-based data ecosystems on Google Cloud Platform, including BigQuery, Bigtable, Dataproc, Pub/Sub, Cloud Storage, IAM, and VPC.
• We design and optimize SQL and NoSQL data models for data lakes and warehouses.
• We write complex SQL queries for advanced transformation, aggregation, and analytics optimization.
• We apply test-driven development methods across big data pipelines and workflow automation.
• We apply data mesh and data-as-a-product principles to create reusable, domain-driven datasets.
• We implement real-time ingestion with Kafka Connect and process streaming data using Spark Streaming, Apache Flink, or similar tools.
• We optimize data performance, scalability, and cost efficiency across cloud components.
• We ensure compliance for PCI and PII data in line with standards such as GDPR, PCI DSS, SOX, and CCPA.
• We integrate GenAI tools such as OpenAI, Gemini, and Anthropic models to enhance data quality and analytics.
• We collaborate with stakeholders, data scientists, and full-stack engineers to deliver trusted, documented, and reusable data products.

• Airflow
• AWS
• Azure
• Big Data
• BigQuery
• Cloud
• ETL
• Flink
• IAM
• Kafka
• NoSQL
• Python
• SQL
• Scala
• Spark
• MongoDB
• Snowflake
• TDD
• XP

More:

We are Kohls, and this Senior Software Engineer role is focused on helping us deliver innovative retail solutions through close collaboration with design, product, and engineering partners. The position combines product engineering with big data responsibilities, including cloud data ecosystems, ETL pipelines, streaming systems, and advanced analytics. We value teamwork, continuous improvement, and technically sound, user-centered software, with opportunities to contribute across the team and department.

last updated 33 week of 2026