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About the Role

Accenture is seeking a strong Data Architect / Data Engineering Lead to provide technical leadership, architectural direction, and engineering governance for enterprise data platform initiatives. This role requires guiding the team on architecture, data engineering best practices, design patterns, governance, data quality, and scalable implementation. The ideal candidate will be an independent thinker capable of evaluating requirements, challenging designs, influencing stakeholders, and ensuring sound data engineering principles are adopted.

Responsibilities

Lead the design of scalable, reliable, and governed data solutions across ingestion, transformation, standardization, and consumption layers.
Define and guide implementation of enterprise data architecture patterns, including Bronze, Silver, and Gold layer design.
Review business requirements and translate them into robust technical and data architecture designs.
Provide architectural guidance on data modeling, data standardization, reusable frameworks, pipeline design, and downstream consumption patterns.
Ensure solutions are designed for scalability, auditability, performance, security, and maintainability.
Establish and enforce production-grade data engineering principles, including idempotency, restartability, observability, auditability, lineage, and automated validation.
Guide the team on proper use of Databricks, Delta Lake, Unity Catalog, orchestration, and lakehouse architecture patterns.
Define standards for pipeline design, naming conventions, audit columns, error handling, data quality checks, and deployment readiness.
Review technical designs and code to ensure adherence to architecture and engineering standards.
Identify and reduce technical debt by promoting reusable, modular, and maintainable implementation patterns.
Define data quality and validation strategies across Bronze, Silver, and Gold layers.
Design exception handling patterns for records that fail validation, have missing mappings, or cannot be standardized.
Ensure mapping, reference, and master data are managed as governed data rather than hardcoded pipeline logic.
Support effective-dated mapping and reference data patterns, audit history, access control, and controlled promotion processes.
Design reprocessing approaches to handle corrected mappings, reference data changes, source changes, late adjustments, and data quality remediation.
Act as a technical lead and mentor for data engineers, helping them think beyond task execution and apply engineering judgment.
Conduct solution design reviews, code reviews, and implementation checkpoints.
Challenge weak or short-term designs constructively and recommend scalable alternatives.
Help the team balance delivery timelines with engineering quality and long-term maintainability.
Create reusable architecture patterns, templates, design checklists, and reference implementations for the team.
Work closely with delivery leads, platform teams, business stakeholders, QA, and data stewards to ensure successful delivery.
Engage with business and IT stakeholders to understand business needs, data challenges, and expected outcomes.
Explain architecture options, tradeoffs, risks, and recommendations in a clear and practical manner.
Proactively identify risks, data gaps, requirement ambiguities, and implementation concerns.
Provide leadership-level visibility into design decisions, data risks, remediation plans, and delivery quality.

Requirements

Minimum of 8 years of experience in enterprise data architecture, data engineering, and lakehouse implementation, with a demonstrated track record of leading architecture efforts on large-scale, enterprise-grade data platforms.
Minimum of 5 years of hands-on experience with Databricks, Delta Lake, PySpark, SQL, and modern cloud data platforms, with the ability to guide technical teams and review implementation quality.
Minimum of 5 years of experience designing and governing production-grade data pipelines with idempotency, restartability, auditability, lineage, monitoring, and exception handling.
Minimum of 4 years of experience with mapping data, reference data, master data, data standardization, and effective-dated design patterns in complex enterprise environments.
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
Strong understanding of Bronze/Silver/Gold architecture, medallion patterns, data modeling, data quality, and data governance.
Ability to design scalable batch, micro-batch, and near-real-time data processing patterns.
Strong SQL and data analysis skills, with the ability to validate data, identify anomalies, and guide root-cause analysis.
Experience with source-to-target mapping, data reconciliation, schema evolution.
Ability to lead design discussions, mentor developers, and influence implementation quality.
Strong communication skills with the ability to interact confidently with business stakeholders and technical teams.
Experience with Unity Catalog, Databricks Workflows, Delta Live Tables / Lakeflow, Auto Loader, Change Data Feed, and materialized views.
Experience with cloud platforms such as Azure, AWS, or GCP.
Experience with data governance, metadata management, cataloging, lineage, and access control.
Experience designing reusable data engineering frameworks and implementation templates.
Experience in trading, commodities, pricing, market data, supply chain, finance, or other complex enterprise data domains is a plus.
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.
At Accenture a criminal conviction history is not an absolute bar to employment.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.
Employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.

Skills

Data Architecture
Data Engineering
Lakehouse Implementation
Databricks
Delta Lake
PySpark
SQL
Cloud Data Platforms
Data Pipelines
Idempotency
Restartability
Auditability
Lineage
Monitoring
Exception Handling
Mapping Data
Reference Data
Master Data
Data Standardization
Effective-dated Design Patterns
Bronze/Silver/Gold Architecture
Medallion Patterns
Data Modeling
Data Quality
Data Governance
Batch Processing
Micro-batch Processing
Near-real-time Processing
Data Analysis
Root-cause Analysis
Source-to-Target Mapping
Data Reconciliation
Schema Evolution
Design Discussions
Mentoring Developers
Stakeholder Communication
Unity Catalog
Databricks Workflows
Delta Live Tables
Lakeflow
Auto Loader
Change Data Feed
Materialized Views
Azure
AWS
GCP
Metadata Management
Cataloging
Access Control
Reusable Data Engineering Frameworks
Implementation Templates
Trading
Commodities
Pricing
Market Data
Supply Chain
Finance

Location

California
Colorado
Connecticut
District of Columbia
Illinois
Maine
Maryland
Massachusetts
Minnesota
New York
New Jersey
Ohio
Virginia
Washington

Work Type

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Experience Level

Minimum of 8 years of experience in enterprise data architecture, data engineering, and lakehouse implementation
Minimum of 5 years of hands-on experience with Databricks, Delta Lake, PySpark, SQL, and modern cloud data platforms
Minimum of 5 years of experience designing and governing production-grade data pipelines
Minimum of 4 years of experience with mapping data, reference data, master data, data standardization, and effective-dated design patterns

Education Level

Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Salary/Compensations

California $94,400 to $293,800
Colorado $94,400 to $253,800
Connecticut $94,400 to $253,800
District of Columbia $100,500 to $270,300
Illinois $87,400 to $253,800
Maine $80,400 to $216,200
Maryland $94,400 to $253,800
Massachusetts $94,400 to $270,300
Minnesota $94,400 to $253,800
New York $87,400 to $293,800
New Jersey $100,500 to $293,800
Ohio $87,400 to $235,000
Virginia $87,400 to $270,300
Washington $100,500 to $270,300

Benefits

Medical, dental, vision, life, and long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

About the Company

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries.
Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships.
We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability.
Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships.
We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com

Equal Opportunity

We have an unwavering commitment to diversity with the aim that every one of our people has a full sense of belonging within our organization.
As a business imperative, every person at Accenture has the responsibility to create and sustain an inclusive environment.
Inclusion and diversity are fundamental to our culture and core values.
Our rich diversity makes us more innovative and more creative, which helps us better serve our clients and our communities.
Accenture is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed.
We believe that no one should be discriminated against because of their differences.
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law.
Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.
Accenture is committed to providing veteran employment opportunities to our service men and women.