Join Deloitte as a Project - Data Engineer in Kansas City, onsite. This role offers a salary range of USD 57,300 - 95,500 per year and a discretionary annual incentive program. You will contribute to the Project Delivery Model by building data pipelines on AWS, maintaining Snowflake objects, safeguarding data quality, and guiding client engagement workstreams. The position sits onsite in Kansas City, MO and provides opportunities to collaborate with cross functional teams while advancing data engineering practices.

Benefits

Discretionary annual incentive program.

The Team

AI & Data - AI and Engineering leverages advanced engineering capabilities to build, deploy, and operate integrated sector solutions across software, data, AI, networks, and hybrid cloud infrastructure. The team focuses on transforming engineering practice to modernize technology and data platforms and to drive business value for clients.

Responsibilities

Build and improve data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
Develop and maintain Snowflake objects (schemas, tables, views) and implement performant SQL transformations to produce curated, analytics-ready datasets.
Implement workflow automation and scheduling with proper dependencies, retries, and logging using tools such as Airflow/MWAA, Step Functions, and Glue.
Apply data quality checks and basic observability, support incident triage and remediation.
Optimize pipeline and query performance with guidance on efficient Python usage, S3 partitioning and file formats, Snowflake warehouse usage, and query tuning.
Follow CI/CD and IaC standards (Git-based workflows, Terraform/CloudFormation) to promote code across environments.
Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs; participate in sprint ceremonies and estimations.
Contribute to code reviews, unit tests, and peer debugging; learn and apply team engineering standards.
Communicate regularly with Engagement Managers, project team members, and stakeholders from various functional and technical teams, escalating as needed.
Independently and collaboratively lead client engagement workstreams aimed at improvement, optimization, and transformation of processes, including implementing leading practice workflows and driving operational outcomes.

Requirements

1+ year of experience building or enhancing data pipelines and curated datasets for analytics and downstream consumers.
1+ year hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
1+ year of cloud data engineering experience on AWS (preferred) or Azure/GCP, including orchestration/scheduling (Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats and partitioning (Parquet/Delta).
Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
Understanding data quality, basic observability, and metadata/governance fundamentals.
Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related IT discipline, or equivalent experience.
Limited immigration sponsorship may be available.
Ability to travel 10% on average, depending on client and project needs.

Technologies

Python
SQL
Snowflake
PySpark
AWS
Airflow / MWAA
Step Functions
Glue
S3
Parquet
Delta
Terraform
CloudFormation
Git
ADF / Fabric Data Factory

Preferred qualifications

Agile delivery experience.
Analytical ability to manage multiple projects and prioritize tasks.
Ability to work independently or with minimal supervision.
Strong written and verbal communication skills.
Ability to deliver technical demonstrations.

Project - Data Engineer