Data Engineer - Project Delivery Analyst
Deloitte
•
Bellevue, WA
0
0
0
0
Not Applicable
Posted March 27, 2026
2 variants
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Responsibilities
Commitments
Responsibilities
- You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.
- Build and enhance 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 performant SQL transformations to produce curated, analytics-ready datasets.
- Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
- Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
- Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
- Follow CI/CD and IaC standards (e.g., 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 (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
- Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
Commitments
Recruiting for this role ends on April 10 th , 2026.
Limited immigration sponsorship may be available.
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.
Can operate independently or with minimum supervision.
Not Met Priorities
What still needs stronger evidence
Requirements
- 1+ year of experience building/enhancing data pipelines and curated datasets for analytics/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 (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
- Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., 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.
- Limited immigration sponsorship may be available.
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred Skills
- 1+ year of experience with cloud data engineering on AWS (preferred) or Azure/GCP, including orchestration/scheduling (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
- Agile delivery experience .
- Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
- Can operate independently or with minimum supervision.
- Excellent written and communication skills.
- Ability to deliver technical demonstrations.
Education
- (Not required) – Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer - Project Delivery Analyst you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.
Recruiting for this role ends on April 10 th , 2026.
Work You'll Do/Responsibilities
You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.
Build and enhance 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 performant SQL transformations to produce curated, analytics-ready datasets.
Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
Follow CI/CD and IaC standards (e.g., 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 (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
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 meet each client's unique requirements.
Qualifications
Required
1+ year of experience building/enhancing data pipelines and curated datasets for analytics/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 (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., 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 the work you do and the clients and industries/sectors you serve.
Preferred
Agile delivery experience .
Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
Can operate independently or with minimum supervision.
Excellent written and communication skills.
Ability to deliver technical demonstrations.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $57,300 to $95,500.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Recruiting for this role ends on April 10 th , 2026.
Work You'll Do/Responsibilities
You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.
Build and enhance 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 performant SQL transformations to produce curated, analytics-ready datasets.
Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
Follow CI/CD and IaC standards (e.g., 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 (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
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 meet each client's unique requirements.
Qualifications
Required
1+ year of experience building/enhancing data pipelines and curated datasets for analytics/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 (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., 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 the work you do and the clients and industries/sectors you serve.
Preferred
Agile delivery experience .
Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
Can operate independently or with minimum supervision.
Excellent written and communication skills.
Ability to deliver technical demonstrations.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $57,300 to $95,500.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.