Based in Rochester, NY and onsite, this role sits within Deloitte's data engineering practice. The Data Engineer – Project Delivery Analyst focuses on building scalable data pipelines on AWS and Snowflake, turning raw data into analytics-ready assets and elevating data quality and observability across delivery teams.

Responsibilities

Construct and optimize AWS-based data pipelines using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
Create and maintain Snowflake objects (schemas, tables, views) and implement efficient SQL transformations to generate curated, analytics-ready datasets.
Automate workflows and scheduling with tools such as Airflow/MWAA, Step Functions, and Glue, ensuring proper dependencies, retries, and logging.
Implement data quality checks and basic observability, including validation rules, reconciliations, and alerts; assist with incident triage and remediation.
Improve pipeline and query performance through best practices in Python efficiency, S3 partitioning/file formats (Parquet/Delta), and Snowflake warehouse tuning.
Adhere to CI/CD and infrastructure-as-code 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; adopt and apply team engineering standards.
Maintain regular communication with Engagement Managers, project members, and cross-functional teams, escalating matters needing engagement management attention.
Lead client engagement workstreams focused on process improvement, optimization, and transformation, including implementing leading practice workflows and driving operational outcomes.

Requirements

At least 1 year of experience building and enhancing data pipelines and curated datasets for analytics and downstream consumers.
Minimum 1 year of hands-on SQL and Python experience, including Snowflake and/or PySpark for transformations and scalable processing.
At least 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).
Comfort with 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.
Sponsorship for immigration may be limited.
Ability to travel approximately 10% of the time, depending on client engagements.

Technologies

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

Benefits

Discretionary annual incentive program, subject to program rules.

The Team

The AI and Data organization at Deloitte brings together engineering capabilities to design, deploy, and operate integrated solutions that span software, data, AI, network, and hybrid cloud infrastructure. The team emphasizes transforming how clients run mission-critical operations by modernizing data platforms and delivery models tailored to each engagement.

PREFERRED

Experience delivering projects in an Agile environment.
Strong analytical ability to juggle multiple projects and translate priorities into actionable work.
Ability to work independently or with minimal supervision.
Excellent written and verbal communication skills.
Capacity to present technical demonstrations effectively.

Project - Data Engineer