24 days ago
Boston, MA, USA +35 moreStaff+
Base Salary
$80k - $294k/yr
Responsibilities
- Lead the architecture and design of scalable, reliable, governed data solutions across ingestion, transformation, standardization, and consumption layers.
- Define and guide Bronze, Silver, and Gold enterprise data architecture and lakehouse patterns.
- Translate business requirements into technical and data architecture designs covering modeling, standardization, reusable frameworks, pipelines, and downstream consumption.
- Establish engineering standards for idempotency, restartability, observability, auditability, lineage, validation, error handling, deployment readiness, and maintainability.
- Guide implementation with Databricks, Delta Lake, Unity Catalog, orchestration, and production-grade data engineering practices.
- Design data quality, exception handling, mapping, reference data, master data, access control, and effective-dated reprocessing strategies.
- Review technical designs and code, identify technical debt, and promote reusable and modular implementation patterns.
- Mentor data engineers and conduct solution design reviews, code reviews, and implementation checkpoints.
- Communicate architecture options, tradeoffs, risks, data gaps, remediation plans, and delivery quality to business and technical stakeholders.
- Collaborate with delivery leads, platform teams, QA, data stewards, and business stakeholders; travel may be required from 0% to 100% depending on business and client needs.
Requirements
- At least 8 years of experience in enterprise data architecture, data engineering, and lakehouse implementation, including leadership of large-scale enterprise data platforms.
- At least 5 years of hands-on experience with Databricks, Delta Lake, PySpark, SQL, and modern cloud data platforms.
- At least 5 years of experience designing and governing production-grade data pipelines with idempotency, restartability, auditability, lineage, monitoring, and exception handling.
- At least 4 years of experience with mapping data, reference data, master data, data standardization, and effective-dated design patterns.
- Bachelor's degree or equivalent minimum 12 years of work experience; candidates with an associate degree must have at least 6 years of work experience.
- Strong knowledge of Bronze/Silver/Gold architecture, medallion patterns, data modeling, data quality, data governance, batch, micro-batch, and near-real-time processing.
- Experience with source-to-target mapping, data reconciliation, schema evolution, anomaly identification, root-cause analysis, and data validation.
- Ability to lead design discussions, mentor developers, influence implementation quality, and communicate effectively with business and technical stakeholders.
- Preferred experience with Unity Catalog, Databricks Workflows, Delta Live Tables or Lakeflow, Auto Loader, Change Data Feed, materialized views, Azure, AWS, or GCP.
- Experience with governance, metadata management, cataloging, lineage, access control, reusable data engineering frameworks, or complex finance and enterprise data domains is preferred.
Benefits
- Medical, dental, vision, life, and long-term disability coverage.
- 401(k) plan and bonus opportunities.
- Paid holidays and paid time off.
- The role may require travel ranging from 0% to 100% based on business need and client requirements.
- The posting is anticipated to remain open through December 31, 2026.
Tech Stack
Categories
Data Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.