Deloitte is seeking a Project - Data Engineer to join its Kansas City onsite team. This role centers on building robust data pipelines on AWS, maintaining Snowflake objects, and safeguarding data quality while guiding client engagement workstreams within the Project Delivery Model. The position offers a salary range of USD 57,300 - 95,500 per year and requires a bachelor’s degree with a minimum of one year of relevant experience.

Responsibilities

Develop and optimize AWS-based data pipelines with Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
Create and maintain Snowflake objects (schemas, tables, views) and implement performant SQL transformations to produce curated, analytics-ready datasets.
Set up workflow automation and scheduling with 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.
Improve pipeline and query performance with guidance on efficient Python practices, S3 partitioning/file formats, and Snowflake warehouse tuning.
Adhere to CI/CD and IaC standards (Git 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; apply team engineering standards.
Communicate regularly with Engagement Managers and project teams, escalating matters that require management attention.
Lead client engagement workstreams, focusing on process improvement, optimization, and transformation to drive operational outcomes.

Requirements

1+ year of experience building and enhancing data pipelines and curated datasets for analytics 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 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 related IT discipline, or equivalent experience.
Limited immigration sponsorship may be available.
Ability to travel about 10% on average, depending on client engagements.

Technologies

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

Benefits

Discretionary annual incentive program.

The Team

AI& Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to mee

Preferred

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

Project - Data Engineer