This on-site role is based in Deloitte’s Rochester, NY delivery hub, where data engineering drives analytics outcomes for clients. The Project - Data Engineer focuses on building and refining data pipelines on AWS and Snowflake, delivering analytics-ready datasets, and boosting data quality and observability within project delivery teams. The salary range for this role is USD 57,300 to 95,500 per year.

Responsibilities

Design and improve AWS-based data pipelines using Python to ingest, transform, and supply data to Snowflake and downstream consumers.
Create and maintain Snowflake schemas, tables, and views, and implement efficient SQL transformations to yield analytics-ready datasets.
Set up workflow automation and scheduling using Airflow or MWAA, Step Functions, or Glue, including dependencies, retries, and logging.
Incorporate data quality checks and basic observability (validation rules, reconciliations, alerts) and assist with incident triage and remediation.
Optimize pipelines and queries following best practices, including efficient Python code, S3 partitioning and file formats (Parquet, Delta), and Snowflake warehouse tuning.
Adhere to CI/CD and IaC standards, utilizing Git-based workflows and Terraform or CloudFormation changes to promote code across environments.
Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs, and participate in sprint ceremonies and estimations.
Contribute to code reviews, write and review unit tests, assist with peer debugging, and adopt team engineering standards.
Communicate regularly with Engagement Managers, Directors, project teammates, and diverse functional or technical stakeholders, escalating issues that require engagement management attention.
Lead client engagement workstreams, independently or with others, focused on process improvement, optimization, and transformation, including implementing best-practice workflows and addressing quality deficits to drive operational outcomes.

Requirements

Over one year of experience building and enhancing data pipelines and curated datasets for analytics and downstream consumers.
At least one year of hands-on SQL and Python experience, including Snowflake and/or PySpark for transformations and scalable processing.
Minimum of one year in cloud data engineering on AWS (preferred) or Azure/GCP, with orchestration/scheduling using Airflow/MWAA, Step Functions, Glue, or ADF/Fabric Data Factory.
Understanding of ELT patterns and lakehouse/warehouse concepts; familiarity with S3 file formats and partitioning such as Parquet or Delta.
Working knowledge of DevOps practices, including Git-based workflows and CI/CD, plus exposure to Infrastructure-as-Code tools such as Terraform or CloudFormation.
Understanding of data quality, basic observability, and metadata/governance fundamentals.
Bachelor’s degree, ideally in computer science, information technology, computer engineering, or a related IT discipline, or equivalent experience.
Limited immigration sponsorship may be available.
Ability to travel approximately 10 percent on average, 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 rules)

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 me

Preferred

Experience delivering projects in Agile environments.
Strong analytical skills to manage multiple projects and prioritize tasks into clear work products.
Ability to work independently or with minimal supervision.
Excellent written and verbal communication skills.
Ability to present technical demonstrations.

Project - Data Engineer