Data Architect / Data Engineering Lead - Finance

1000 Accenture LLP Company; Chicago (IL); On-site; USD 87,000 - 254,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Long-term disability coverage

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking a senior Data Architect / Data Engineering Lead to guide enterprise data platform initiatives. You will set architectural direction, govern data pipelines, and mentor a team of data engineers across ingestion, transformation, and consumption layers.

The role requires deep experience in data architectures (Bronze-Silver-Gold), Databricks, Delta Lake, PySpark, and SQL, with a focus on scalable, auditable, and secure solutions. Travel may be required.

Qualifications

• Minimum of 8 years of enterprise data architecture, data engineering, and lakehouse implementation.
• Minimum of 5 years hands-on experience with Databricks, Delta Lake, PySpark, SQL, and modern cloud data platforms.
• Minimum of 5 years designing and governing production-grade data pipelines with idempotency, restartability, auditability, lineage, monitoring, and exception handling.
• Minimum of 4 years experience with mapping, reference, and master data, data standardization, and effective-dated design patterns.
• Bachelor's degree or equivalent (minimum 12 years) work experience.

Responsibilities

• Provide architectural leadership for scalable, governed data solutions across ingestion, transformation, and consumption layers.
• Define and enforce data engineering standards, quality checks, and lineage for enterprise pipelines.
• Mentor engineers, review designs, and ensure alignment with governance and security requirements.
• Collaborate with stakeholders to translate business needs into robust data architecture patterns.

Skills

Data architecture

Data engineering

Leadership

Problem solving

Communication

Education

Bachelor's degree or equivalent

Tools

Databricks

Delta Lake

PySpark

SQL

Job description

We Are The beginning of a newData &AI decade that will reshape work and societyhas begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clientsoptimizeand reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work. With over45,000professionals dedicated toData & AI,Accenture’s Data & AI organizationbrings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem. You are A strong Data Architect / Data Engineering Lead who can provide technical leadership, architectural direction, and engineering governance for enterprise data platform initiatives. This role is not intended for a hands‑on‑only developer profile. The ideal candidate should be able to guide the team on overall architecture, data engineering best practices, design patterns, governance, data quality, and scalable implementation approaches. The candidate should be an independent thinker who can evaluate requirements, challenge weak designs, influence stakeholders, and ensure that sound data engineering principles are consistently adopted across the team. The Work Architecture and Design Leadership 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. Data Engineering Best Practices 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. Data Quality, Governance, and Standardization 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 (e.g., chart of accounts, cost center, product, and customer hierarchies) 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 (e.g., financial restatements or prior‑period corrections), and data quality remediation. Leadership and Team Enablement 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. Stakeholder Communication 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. Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here’s what you need

• 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)

Professional Skills Requirements: 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 (e.g., to source control totals or general ledger balances), 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.

Bonus if you have

• 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 (e.g., financial close, management reporting), or other complex enterprise data domains is a plus.

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below. We anticipate this job posting will be posted until 12/31/2026. Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long‑term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here: U.S. Employee Benefits | Accenture Role Location Annual Salary Range

• medical
• dental
• vision
• life
• long‑term disability coverage
• 401(k) plan
• bonus opportunities
• paid holidays
• paid time off

• 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

About Accenture

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.

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