Sr. Data Engineer

Conagra Brands•Chicago, IL

20h•$94,300 - $138,000•Hybrid

About The Position

Reporting to the Manager of Advanced Analytics and Enterprise Insights, you will lead the development, optimization, and delivery of data pipelines and workflows that support our Enterprise Data Platform. You will apply strong data engineering fundamentals alongside software engineering and DevOps practices to ensure pipelines are built, deployed, and monitored as code. You will play a key role in enabling high-quality, reliable, and accessible data that drives informed decision-making across the organization while partnering with cross-functional teams to deliver impactful data solutions.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related field.
5–8 years of experience in data engineering or a related role.
Advanced proficiency in structured query language for complex data transformation and analysis.
Experience with cloud-based data platforms such as Databricks, Snowflake, or similar technologies.
Experience with extract, transform, and load or extract, load, transform tools and frameworks such as Informatica, Talend, dbt, or equivalent.
Strong proficiency in Python or PySpark for data processing and pipeline development.
Strong understanding of data modeling, database design, and building curated datasets for analytics and operational use.
Experience with DevOps practices and Git-based development including branching strategies, pull requests, and code reviews.
Experience implementing continuous integration and continuous deployment for data pipelines and managing multi-environment deployments.
Familiarity with orchestration and workflow tools such as Databricks Workflows, Airflow, or similar platforms.
Familiarity with Infrastructure as Code tools such as Terraform or CloudFormation.
Strong problem-solving skills with attention to detail and end-to-end troubleshooting.
Strong communication skills and collaboration across technical and non-technical teams.

Responsibilities

Lead the design, development, and maintenance of scalable data pipelines that integrate data from multiple sources into the Enterprise Data Platform.
Build pipelines and workflows as code using modern engineering practices including version control, code reviews, automated testing, and reusable components.
Define and implement continuous integration and continuous deployment patterns for data pipelines, including automated builds, testing, deployments, and environment promotion.
Partner with data scientists, analysts, and business stakeholders to gather requirements and translate them into robust, scalable data solutions.
Build and optimize structured query language queries and transformations to support complex analytics and business use cases.
Design and manage data models, validating them with stakeholders, architects, and governance partners.
Establish data quality checks, validation frameworks, and troubleshooting practices to ensure accuracy, consistency, and trust in data products.
Monitor and optimize pipeline performance and reliability, implementing logging, metrics, alerting, and operational runbooks.
Drive automation to improve efficiency, reduce manual effort, and increase repeatability of platform operations.
Provide technical leadership by mentoring engineers, conducting code reviews, and promoting best practices and standards.
Participate in Agile ceremonies to plan, estimate, and deliver work effectively.
Create and maintain documentation for data workflows, transformations, standards, and operational procedures.