
Data Engineer - Project Delivery Analyst
Deloitte · Baltimore, MD
- On site
- Full-time
- $75,000 / year
- Baltimore, MD
Job highlights
- Build and enhance data pipelines on AWS.
- Develop and maintain Snowflake data structures.
- Implement workflow automation and scheduling.
- Collaborate with cross-functional teams on projects.
- Analyze and optimize pipeline performance.
About the role
Data Engineer - Project Delivery Analyst
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 30th, 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) 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.
Compensation
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.
Key skills/competency
- Data Engineering
- AWS
- Python
- SQL
- Snowflake
- Data Pipelines
- ETL/ELT
- DevOps
- Cloud Data Engineering
- Project Delivery
Skills & topics
- Data Engineer
- AWS
- Python
- SQL
- Snowflake
- Data Pipelines
- Cloud Engineering
- Project Delivery
- ETL
- DevOps
How to get hired
- Tailor your resume: Highlight your 1+ year of experience with data pipelines, SQL, Python, and AWS cloud data engineering, emphasizing Snowflake and orchestration tools.
- Showcase relevant skills: Quantify your achievements in building and enhancing data pipelines, data transformations, and cloud environments.
- Understand Deloitte's PDM: Familiarize yourself with the Project Delivery Model for long-term, onsite client service delivery.
- Prepare for technical questions: Be ready to discuss your experience with ELT patterns, Lakehouse concepts, DevOps practices, and data quality fundamentals.
- Demonstrate collaboration: Emphasize your ability to work with analysts, product owners, and other technical teams in an Agile environment.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific cloud platforms does Deloitte prefer for this Data Engineer role?
- While AWS is preferred for this Data Engineer Project Delivery Analyst role, Deloitte also has experience with Azure and GCP. Highlighting your experience with any of these cloud platforms will be beneficial.
- How important is experience with Snowflake for this Data Engineer position at Deloitte?
- Experience with Snowflake is highly valued for this Data Engineer role, as you will be developing and maintaining Snowflake objects and performing SQL transformations. Proficiency in Snowflake is a key requirement.
- What does 'Project Delivery Talent Model' mean for a Data Engineer at Deloitte?
- The Project Delivery Talent Model (PDM) means this Data Engineer role is focused on long-term, onsite client service delivery, offering a collaborative environment without extensive travel demands.
- Does Deloitte offer immigration sponsorship for the Data Engineer position?
- Limited immigration sponsorship may be available for this Data Engineer Project Delivery Analyst position. It's advisable to inquire further about specific sponsorship details during the application process.
- What is the typical career progression for a Data Engineer at Deloitte?
- As a Data Engineer at Deloitte, career progression can involve moving into more senior engineering roles, technical leadership positions, or specializing in areas like AI & Engineering. The Project Delivery Model also offers opportunities for growth within client engagements.
- What are the main responsibilities of a Data Engineer - Project Delivery Analyst at Deloitte?
- Key responsibilities include building and enhancing data pipelines on AWS using Python, developing Snowflake objects and SQL transformations, implementing workflow automation, and collaborating with various teams to deliver data solutions.
- How does Deloitte handle work-life balance for its Data Engineers?
- Deloitte's Project Delivery Model aims to provide a better work-life balance by focusing on long-term, onsite client delivery, reducing the extensive travel often associated with consulting roles.
- What kind of collaboration can I expect as a Data Engineer at Deloitte?
- You can expect a highly collaborative environment, working closely with analysts, product owners, source-system teams, and other project members in sprint ceremonies and code reviews.