[Remote] Senior Data Engineer (Remote)
Note: The job is a remote job and is open to candidates in USA. Kohl's is seeking a Senior Data Engineer to collaborate with design, product, and engineering teams to enhance their retail offerings. The role involves leading the development of robust applications, managing cloud-based data ecosystems, and implementing data pipelines while ensuring compliance with data standards.
Responsibilities
- Lead the development of high-quality applications that are robust, observable and measurable using extreme programming (XP) practices and a user-centric approach
- Participate in the entire application lifecycle in collaboration with designers, product managers, and other engineers on the product team
- Leverage critical thinking, experimentation, data, and industry best practices to implement desired business outcomes
- Facilitate group discussions and team ceremonies and develop a shared context
- Give and receive feedback that’s empathetic, actionable and specific
- Practice emergent architecture with sane defaults and build software that is easy to use and easy to modify
- Establish and lead product engineering and software standards
- Ideate a new product from a user perspective, starting with one or more problem spaces and ending with a stack-ranked list of feasible solutions to test
- Research and stay up to date on tech market trends and practices
- Lead technical initiatives not only on the team but also across the department
- Develop, automate, and maintain batch and streaming ETL pipelines using Apache Airflow, Apache Spark, Python, and Scala
- Build and manage cloud-based data ecosystems on GCP (BigQuery, Bigtable, Dataproc, Pub/Sub, Cloud Storage, IAM, VPC)
- Design and optimize SQL and NoSQL data models for data lakes and warehouses (BigQuery, MongoDB, Snowflake)
- Write complex SQL queries for advanced data transformation, aggregation, and analytics optimization within BigQuery or equivalent platforms
- Apply modern Test-Driven Development (TDD) methodologies for big data pipelines, ensuring test automation across Airflow workflows, Spark jobs, and transformation logic
- Apply data mesh and data-as-a-product principles to enable reusable and domain-driven datasets
- Implement real time ingestion with Kafka Connect and process streaming data using Spark Streaming, Apache Flink, or similar technologies
- Optimize data performance, scalability, and cost efficiency across GCP components
- Ensure compliance with PCI and PII data with standards such as GDPR, PCI DSS, SOX, and CCPA
- Integrate GenAI tools such as OpenAI, Gemini, and Anthropic LLMs for intelligent data quality and analytics enhancement
- Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted, documented, and reusable data products
Skills
- 4+ years of experience in software development
- Understanding of application design patterns, event-driven architecture, database, schemas and testing strategies
- In-depth knowledge and experience with continuous integration, continuous deployment and test-driven development
- Bachelor's Degree or equivalent in MIS, Computer Science or related field
- Experience with large-scale application troubleshooting and performance tuning
- Exposure working with major cloud platforms (GCP, AWS, or Azure)
- Familiarity and experience with XP (Extreme Programming)
Company Overview
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