Project - Data Engineer

Deloitte is seeking a Data Engineer to join the Project Delivery Model, building and refining data pipelines that transform raw data into analytics-ready datasets on AWS and Snowflake. This onsite role based in Bellevue, WA collaborates with analysts, product owners, and source-system teams to deliver impactful data solutions, with a salary range of USD 57,300 to 95,500 per year and a bachelor’s degree as the baseline requirement.

Responsibilities

• Design and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
• Create and maintain Snowflake objects (schemas, tables, views) and develop performant SQL transformations to produce curated datasets ready for analytics.
• Implement workflow automation and scheduling with dependencies, retries, and logging using tools such as Airflow/MWAA, Step Functions, or Glue.
• Apply data quality checks and basic observability, support incident triage and remediation, and ensure data integrity across pipelines.
• Optimize pipeline and query performance with guidance on efficient Python practices, S3 partitioning and formats, and Snowflake warehouse usage and tuning.
• Adhere to CI/CD and IaC standards, including 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, validate outputs, and participate in sprint ceremonies and estimations.
• Contribute to code reviews, unit tests, and peer debugging while applying team engineering standards and best practices.
• Maintain regular communication with Engagement Managers, project team members, and cross-functional stakeholders, escalating issues as needed for engagement management.
• Lead client engagement workstreams independently or collaboratively, driving process improvements, optimization, and transformation using leading practice workflows and quality improvements.

Requirements

• 1+ year of experience building or enhancing data pipelines and curated datasets for analytics or downstream consumption.
• 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, 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 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.

Technologies

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