Top Data Engineer Jobs in Kansas City, MO

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

Design, build, and maintain scalable, reliable data pipelines and services. Write well-tested Python and SQL code, work with orchestration (Airflow), containers, and cloud infrastructure. Collaborate cross-functionally to deliver data products and improve development processes.

Build and maintain Databricks-based ETL/ELT pipelines, transform and model data, optimize workflows, monitor and troubleshoot pipelines, and collaborate with cross-functional teams.

The Principal Data Engineer will design and implement enterprise data frameworks, mentor teams, and ensure data quality while collaborating with stakeholders.

The Data Engineer I will manage data warehouses, extend data pipelines, write SQL and Python scripts, and support data operations.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

The Data Engineer III will design and maintain data infrastructure, ensuring efficient data loading and compliance while mentoring junior engineers and collaborating with Analytics teams.

The Principal Data Engineer will lead data governance, architecture, and team development to unify data across systems while ensuring quality and compliance. Responsibilities include building data pipelines, establishing governance frameworks, and collaborating with cross-functional teams to drive data-driven insights and operational efficiencies.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

The Data QA Engineer designs and executes test plans for data pipelines and transformations, collaborates with teams to ensure data quality, and utilizes AI techniques for testing automation. They validate business metrics and facilitate cross-team communication.

The Software Engineer will develop and enhance Research platforms, leverage data science, and work with cross-functional teams to create scalable, maintainable systems for data products at Netflix.

The Staff Data Engineer will design data architecture, develop scalable data pipelines, ensure data quality, and lead governance practices while collaborating across teams.

The Senior Data Engineer will design and maintain scalable data pipelines, lead medium-sized platform projects, and ensure reliability of data systems through monitoring and optimization. Responsibilities include working with cross-functional teams to improve data workflows and participate in incident response.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

The Staff Data Engineer will architect and implement a next-generation data platform, build data pipelines, and ensure data integrity for actionable insights.

As a Senior Data Engineer, you will design ETLs for large customer datasets, improve integration tools, and mentor other engineers, impacting customer onboarding and data accuracy.

As a Data Engineer, you will build and maintain data pipelines, improve customer integrations, and collaborate with teams to deliver data solutions that reduce food waste.

The Senior Engineer, Data will architect and deploy data pipelines, optimize databases, collaborate with teams, and maintain data integrity. They will also enhance data architecture and improve processes using various technologies.

As a Staff Software Engineer in Data Engineering, you will design, build, and optimize robust data systems to ensure data quality, performance, and stability, while mentoring team members and collaborating with cross-functional teams.