Based onsite in Kansas City, MO, Deloitte's Project Delivery team is looking for a Data Engineer to build data pipelines on AWS, maintain Snowflake objects, ensure data quality, and lead client engagement workstreams. Salary range: USD 57,300 to 95,500 per year. A Bachelor's degree and at least 1 year of relevant experience are required.

Benefits

Discretionary annual incentive program.

Responsibilities

Build and refine 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 write performant SQL transformations to produce curated, analytics-ready datasets.
Implement workflow automation and scheduling with proper dependencies, retries, and logging using Airflow/MWAA, Step Functions, and Glue.
Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
Optimize pipeline and query performance with guidance on efficient Python, S3 partitioning, and Snowflake warehouse usage and query tuning.
Follow CI/CD and IaC standards (Git-based workflows, Terraform/CloudFormation changes) 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 (Directors), project team members, and cross-functional technical teams; escalate matters needing engagement management attention.
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes, 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 of hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
1+ year of experience with 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, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
Limited immigration sponsorship may be available.
Ability to travel 10% on average, based on work and client needs.

Technologies

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

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