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Data Engineer Project information

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$46K

$165K

$243.5K

How much do data engineer project jobs pay per year?

As of May 30, 2026, the average yearly pay for data engineer project in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need strong proficiency in programming (Python, Java, or Scala), data modeling, and database management, often supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), ETL systems, cloud platforms (AWS, Azure, GCP), and relevant certifications is highly beneficial. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with data teams and stakeholders. These competencies are essential for building reliable data pipelines and ensuring data availability and quality to drive business insights.

What are some common challenges faced by Data Engineers working on project-based teams?

Data Engineers on project-based teams often encounter challenges such as integrating data from disparate sources, ensuring data quality and consistency, and meeting tight project deadlines. Collaboration with data scientists, analysts, and software engineers is crucial, requiring clear communication to translate business needs into robust data pipelines. Additionally, adapting to evolving technologies and toolsets is essential for the successful delivery of scalable and maintainable solutions.

What is a Data Engineer Project?

A Data Engineer Project refers to a specific initiative or assignment undertaken by data engineers to design, build, and maintain systems that gather, process, and store large volumes of data. These projects often involve creating data pipelines, integrating multiple data sources, ensuring data quality, and optimizing storage solutions for analytics or business intelligence. Such projects are critical for organizations to manage their data efficiently and enable data-driven decision-making. Data Engineer Projects can range from building a data warehouse to implementing real-time data streaming solutions.

What is the difference between Data Engineer Project vs Data Engineer?

AspectData Engineer ProjectData Engineer
CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; certifications like AWS, Google Cloud, or Azure are commonSimilar credentials; often holds certifications in cloud platforms and data tools
Work EnvironmentProject-based, often temporary teams working on specific data solutionsFull-time role within organizations, maintaining ongoing data pipelines and infrastructure
Industry UsageUsed across industries for specific data initiativesCore role in data-driven companies and departments
Search & Comparison IntentOften searched for project-based roles or freelance opportunitiesMore common in job searches for permanent positions

In summary, Data Engineer Projects focus on temporary, goal-specific data tasks, while Data Engineers hold ongoing roles responsible for maintaining data infrastructure. Both roles require similar skills and certifications but differ mainly in scope and employment type.

More about Data Engineer Project jobs
What cities are hiring for Data Engineer Project jobs? Cities with the most Data Engineer Project job openings:
What states have the most Data Engineer Project jobs? States with the most job openings for Data Engineer Project jobs include:
Data Engineer - Project Delivery Analyst

Data Engineer - Project Delivery Analyst

Deloitte

Stamford, CT

Other

Posted 13 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

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 May 31st, 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.

Qualifications:

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 May 31st, 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.

Education:Bachelor's DegreeEmployment Type:

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