The Role
Lead architecture, design, and delivery of enterprise Snowflake data platforms. Build and operate ingestion and transformation pipelines (batch and streaming), define data modeling and governance standards, implement CI/CD and IaC, optimize performance and cost, enforce security/compliance, and mentor engineers to deliver scalable data products for analytics, AI/ML, and operational use cases.
Summary Generated by Built In
Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Data Engineering, Snowflake Data Warehouse
Good to have skills : Machine Learning (ML)
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
Lead the architecture, strategy, and delivery of enterprise-scale data platforms on Snowflake. Own
technical direction for data modeling, ingestion, performance, security, governance, and developer
experience. Mentor engineers and collaborate with stakeholders to deliver robust, scalable, and
secure data solutions for analytics, AI/ML, and operational use cases.
Roles and responsibilities:
Architecture & Strategy
Define target data platform architecture (multi-environment, multi-account, integration
patterns).
Establish technical standards for ELT, dbt/Snowpark, data contracts, and lifecycle
management.
Lead make/buy/standardize decisions for connectors, CDC/integration tools, orchestration,
catalog, and observability.
Design and Implement CI/CD pipelines for data engineering workflows
Design and Implement Streaming data architectures and Micro-service based architectures
Design and implement reliable ingestion and transformation pipelines (batch/streaming) using
Snowflake features (Snowpipe, Streams & Tasks, external stages) and orchestration tools
(Airflow/ADF).
Drive data modeling best practices (dimensional, data vault, wide tables) with versioning,
testing, and documentation.
Enable CI/CD, environment promotion, automated data quality checks (dbt tests, Great
Expectations), and blue-green deployments.
Performance, Reliability & Cost
Lead workload management, query optimization, clustering, and caching strategies.
Implement resource monitors, autosuspend policies, and cost observability dashboards.
Own SLA/SLOs for key data products, incident runbooks, lineage-aware impact analysis, and
post-incident reviews.
Security, Compliance & Sharing
Define and enforce RBAC/ABAC, row/column-level security, masking policies, and secrets
management.
Partner with Security/GRC on auditing, data retention, PII/PHI protection, and regulatory
compliance (GDPR/CCPA).
Operationalize secure data sharing and cleanroom patterns for internal/external collaboration.
Leadership & Influence
Serve as principal technical authority for Snowflake mentor engineers and elevate team
capability.
Collaborate with Product, Analytics, and ML teams to deliver scalable, reusable data products.
Author architecture decision records (ADRs), roadmaps, and executive-level technical
narratives.
Technical experience & Professional attributes:
12+ years in data engineering/architecture 6+ years designing and operating Snowflake at scale
(multi-TB warehouses, 1000s of daily jobs).
Expert SQL and deep knowledge of Snowflake internals: virtual warehouses, micropartitions,
clustering, Query Profile, caching, Time Travel, Failsafe.
Hands-on with Snowflake workloads & features: Snowpipe, Streams & Tasks, stages/external
tables, materialized views, Secure Data Sharing.
Experience with at least one transformation framework (dbt strongly preferred) and
programming language (Python, Snowpark, UDFs).
Experience with orchestration (Airflow/ADF/Argo), CI/CD (Jenkins/GitHub Actions/GitLab/Azure
DevOps), and IaC (Terraform).
Fluency with cloud platforms (AWS/Azure/GCP), object storage (S3/ADLS/GCS), networking
(VPC/VNet, PrivateLink/Private Endpoints).
Solid grounding in data governance (catalog/lineage tools), privacy & security controls, and
observability (logs/metrics/traces for pipelines).
Experience in Fivetran and streaming tools Kafka, Pulsar or other equivalent.
Performance tuning at scale: warehouse sizing, task concurrency, pruning/clustering, cost
optimization.
Excellent communication able to present architecture tradeoffs to engineers and executives.
Preferred Skills
SnowPro Advanced: Architect or Advanced: Data Engineer certification.
Data quality frameworks ,data contracts, and contract-testing patterns.
Additional Information:
You will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions
Strategic Leadership: Ability to influence technology direction and align solutions with business objectives.
Mentorship & Talent Development: Guide and coach engineers foster an inclusive and high-performing team culture.
Excellent Communication Skills: Strong verbal, written, and presentation skills for technical and non-technical audiences.
Business Acumen: Understand business priorities and translate them into actionable technical strategies.
Change Management & Stakeholder Engagement: Drive adoption of new processes and manage organizational change effectively.
Decision-Making & Problem-Solving: Demonstrate sound judgment in complex, ambiguous situations.15 years full time education
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Data Engineering, Snowflake Data Warehouse
Good to have skills : Machine Learning (ML)
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
Lead the architecture, strategy, and delivery of enterprise-scale data platforms on Snowflake. Own
technical direction for data modeling, ingestion, performance, security, governance, and developer
experience. Mentor engineers and collaborate with stakeholders to deliver robust, scalable, and
secure data solutions for analytics, AI/ML, and operational use cases.
Roles and responsibilities:
Architecture & Strategy
Define target data platform architecture (multi-environment, multi-account, integration
patterns).
Establish technical standards for ELT, dbt/Snowpark, data contracts, and lifecycle
management.
Lead make/buy/standardize decisions for connectors, CDC/integration tools, orchestration,
catalog, and observability.
Design and Implement CI/CD pipelines for data engineering workflows
Design and Implement Streaming data architectures and Micro-service based architectures
Design and implement reliable ingestion and transformation pipelines (batch/streaming) using
Snowflake features (Snowpipe, Streams & Tasks, external stages) and orchestration tools
(Airflow/ADF).
Drive data modeling best practices (dimensional, data vault, wide tables) with versioning,
testing, and documentation.
Enable CI/CD, environment promotion, automated data quality checks (dbt tests, Great
Expectations), and blue-green deployments.
Performance, Reliability & Cost
Lead workload management, query optimization, clustering, and caching strategies.
Implement resource monitors, autosuspend policies, and cost observability dashboards.
Own SLA/SLOs for key data products, incident runbooks, lineage-aware impact analysis, and
post-incident reviews.
Security, Compliance & Sharing
Define and enforce RBAC/ABAC, row/column-level security, masking policies, and secrets
management.
Partner with Security/GRC on auditing, data retention, PII/PHI protection, and regulatory
compliance (GDPR/CCPA).
Operationalize secure data sharing and cleanroom patterns for internal/external collaboration.
Leadership & Influence
Serve as principal technical authority for Snowflake mentor engineers and elevate team
capability.
Collaborate with Product, Analytics, and ML teams to deliver scalable, reusable data products.
Author architecture decision records (ADRs), roadmaps, and executive-level technical
narratives.
Technical experience & Professional attributes:
12+ years in data engineering/architecture 6+ years designing and operating Snowflake at scale
(multi-TB warehouses, 1000s of daily jobs).
Expert SQL and deep knowledge of Snowflake internals: virtual warehouses, micropartitions,
clustering, Query Profile, caching, Time Travel, Failsafe.
Hands-on with Snowflake workloads & features: Snowpipe, Streams & Tasks, stages/external
tables, materialized views, Secure Data Sharing.
Experience with at least one transformation framework (dbt strongly preferred) and
programming language (Python, Snowpark, UDFs).
Experience with orchestration (Airflow/ADF/Argo), CI/CD (Jenkins/GitHub Actions/GitLab/Azure
DevOps), and IaC (Terraform).
Fluency with cloud platforms (AWS/Azure/GCP), object storage (S3/ADLS/GCS), networking
(VPC/VNet, PrivateLink/Private Endpoints).
Solid grounding in data governance (catalog/lineage tools), privacy & security controls, and
observability (logs/metrics/traces for pipelines).
Experience in Fivetran and streaming tools Kafka, Pulsar or other equivalent.
Performance tuning at scale: warehouse sizing, task concurrency, pruning/clustering, cost
optimization.
Excellent communication able to present architecture tradeoffs to engineers and executives.
Preferred Skills
SnowPro Advanced: Architect or Advanced: Data Engineer certification.
Data quality frameworks ,data contracts, and contract-testing patterns.
Additional Information:
You will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions
Strategic Leadership: Ability to influence technology direction and align solutions with business objectives.
Mentorship & Talent Development: Guide and coach engineers foster an inclusive and high-performing team culture.
Excellent Communication Skills: Strong verbal, written, and presentation skills for technical and non-technical audiences.
Business Acumen: Understand business priorities and translate them into actionable technical strategies.
Change Management & Stakeholder Engagement: Drive adoption of new processes and manage organizational change effectively.
Decision-Making & Problem-Solving: Demonstrate sound judgment in complex, ambiguous situations.15 years full time education
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.Visit us at www.accenture.com
Equal Employment Opportunity Statement
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. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- Data Engineering
- Snowflake Data Warehouse (architecture and operations at scale)
- Minimum 12 years experience in data engineering/architecture
- 15 years full time education
- 6+ years designing and operating Snowflake at scale
- Expert SQL and deep knowledge of Snowflake internals (virtual warehouses, micropartitions, clustering, caching)
- Hands-on with Snowflake features: Snowpipe, Streams & Tasks, external stages/tables, materialized views, Secure Data Sharing
- Experience with transformation frameworks and testing (dbt strongly preferred; dbt tests)
- Programming experience: Python, Snowpark, UDFs
- Orchestration experience: Airflow, Azure Data Factory (ADF), or Argo
- CI/CD experience (Jenkins, GitHub Actions, GitLab, Azure DevOps)
- Infrastructure as Code (Terraform)
- Fluency with cloud platforms (AWS, Azure, GCP) and object storage (S3, ADLS, GCS)
- Networking knowledge (VPC/VNet, PrivateLink/Private Endpoints)
- Data quality frameworks and contract-testing patterns (Great Expectations, data contracts)
- Experience with Fivetran and streaming tools (Kafka, Pulsar or equivalent)
- Performance tuning at scale: warehouse sizing, task concurrency, pruning/clustering, cost optimization
- Strong communication, leadership, mentorship, and ability to present architecture tradeoffs to executives
- Machine Learning (ML)
- SnowPro Advanced: Architect or Advanced: Data Engineer certification
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
-
Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
-
Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
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The Company
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
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