Project - Data Engineer

Deloitte is seeking a Project - Data Engineer to join their delivery team on site in Stamford, CT. The role centers on building robust data pipelines and analytics-ready datasets in AWS and Snowflake for a large, onshore/offshore program, with CI/CD, observability, and collaboration across analytics and product teams.

Responsibilities

• Design and enhance 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 produce curated analytics-ready datasets.
• Set up workflow automation and scheduling across MWAA Airflow, Step Functions, and Glue, including dependencies, retries, and logging.
• Implement data quality checks and basic observability, including validation rules, reconciliation, and alerts, and assist with incident triage and remediation.
• Improve pipeline and query performance through best-practice techniques, such as efficient Python, S3 partitioning and file formats, and Snowflake tuning.
• Adhere to CI/CD and Infrastructure-as-Code standards using Git workflows and Terraform/CloudFormation to promote code across environments.
• Collaborate with analysts, product owners, and source-system teams to clarify requirements, validate outputs, and participate in sprint ceremonies and estimations.
• Contribute to code reviews, unit tests, and peer debugging while applying the team engineering standards.
• Maintain regular communication with Engagement Managers, project team members, and various functional/technical stakeholders, escalating issues when needed.
• Lead client engagement workstreams, focusing on process improvement, optimization, and transformation by implementing leading-practice workflows and driving operational outcomes.

Requirements

• 1+ year of experience building and refining data pipelines and curated datasets for analytics and downstream consumers.
• 1+ year of hands-on SQL and Python experience, including Snowflake and/or PySpark for transformations and scalable processing.
• 1+ year of cloud data engineering experience on AWS (preferred) or Azure/GCP, with orchestration/scheduling tools such as 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 (Parquet/Delta).
• Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
• Understanding of 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 approximately 10% depending on client engagements.
• Agile delivery experience.
• Analytical ability to manage multiple projects and prioritize tasks.
• Ability to work independently or with minimal supervision.
• Excellent written and verbal communication skills.
• Ability to deliver technical demonstrations.

Technologies

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

Benefits

• Discretionary annual incentive program

The Team

AI & Data - AI & Engineering leverages advanced engineering capabilities to build, deploy, and operate integrated sector solutions across software, data, AI, networks, and hybrid cloud infrastructure. These solutions empower clients to modernize technology and data platforms while transforming engineering teams and delivering operational value.