You’ve Never Been Satisfied with “Good Enough.”
You want to make an impact, not just manage projects, but change how the world gets built. At Accenture Infrastructure & Capital Projects, you’ll do exactly that. You’ll help develop and deliver the factories, grids, transit systems, and public infrastructure that keep communities moving - and do it smarter, safer, and more sustainably than ever before.
You’ll work alongside people who think big and act bold - project managers, engineers, technologists, and strategists who blend real-world experience with digital innovation and AI. Together, we’re transforming how capital projects are planned, managed, and executed, creating a better way to build for the future.
Because “good enough” builds the past. You’re here to build what’s next, on a team that outperforms every norm.
Visit us here to learn more about Accenture Infrastructure & Capital Projects
About the Role:
We are seeking a Data Engineer to support large-scale capital infrastructure programs, with a strong focus on data transformation and preparation to enable trusted, analytics-ready datasets for Power BI reporting.
This role sits at the intersection of data ingestion, transformation, and analytics enablement, supporting engagements where owners consolidate data from internal enterprise systems and external supply-chain sources. Much of the value in this role comes from cleaning, standardizing, and conforming inconsistent data into common structures that support portfolio-level and executive reporting.
You will work closely with Data & Analytics Consultants and BI Developers to design robust ingestion and transformation frameworks using Azure Data Factory (ADF), curate analytics-ready data in Snowflake, and ensure downstream Power BI reporting is accurate, performant, and scalable.
- (Internal Title: Business System Configuration / Development III)
- Data Transformation & Preparation
- Design and implement data transformation logic to cleanse, standardize, and conform data from both internal enterprise systems and external supply-chain sources.
- Normalize inconsistent supply-chain data into common dimensions, reference data, and standardized KPI definitions.
- Implement business rules, derivations, and calculations to ensure consistency across reports and dashboards.
- Manage slowly changing dimensions (SCDs), snapshots, and historical views to support trend and time-series analysis.
- Ensure all transformed datasets are analytics-ready and aligned to defined reporting use cases.
- Analytics Enablement & Reporting Support
- Deliver Power BI–ready datasets aligned to standardized KPIs and reporting requirements.
- Design and maintain analytics-focused data models (facts, dimensions, snapshots) optimized for reporting performance.
- Support Power BI refresh strategies, including incremental refresh and dependency sequencing.
- Partner closely with BI developers and analysts to ensure semantic consistency between Snowflake data models and Power BI measures.
- Work within the client’s Snowflake and Power BI environment, writing complex SQL transformations to prepare EPC and PMIS data (e.g., Oracle Primavera P6 and related systems) for reporting.
- Data Engineering & Architecture
- Develop and maintain end-to-end ELT pipelines using Azure Data Factory (ADF) into Snowflake, in support of transformation and reporting needs.
- Implement incremental loads, change data capture (CDC), and historical tracking to enable time-based analysis.
- Support scalable and maintainable data architectures aligned to enterprise analytics standards.
- Internal & Supply Chain Data Ingestion Automation (Enabling Capability)
- Design and implement automated ingestion pipelines for: Internal enterprise systems (e.g., PMIS, ERP, scheduling, commercial systems), and External supply-chain data (e.g., contractor cost, progress, schedule, commercial, and performance data).
- Handle ingestion from heterogeneous sources, including databases, flat files, APIs, and shared data environments.
- Build reusable Azure Data Factory (ADF) pipeline templates to support multi-system, multi-vendor, and multi-project ingestion patterns.
- Implement validation, reconciliation, and exception handling to manage inconsistent, late, or partial data submissions.
- Data Quality, Governance & Reliability
- Embed automated data quality checks within ingestion and transformation pipelines.
- Monitor pipeline execution and proactively address failures, anomalies, and data integrity issues.
- Support data lineage, documentation, and governance standards across both internal and externally sourced data.
- Enforce consistent data structures, naming conventions, and KPI definitions.
- Process Oversight & Delivery
- Collaborate with technical teams to monitor CI/CD pipelines (GitHub / Azure DevOps) and troubleshoot issues impacting reporting availability.
- Work closely with Data & Analytics Consultants to translate reporting requirements into scalable transformation and modeling solutions.
- Participate in Hybrid-Agile delivery, including sprint planning, backlog refinement, and iterative releases.
- Contribute to CI/CD practices for ADF pipelines, Snowflake objects, and analytics assets.
- Working Conditions:
- Hybrid: this role's work location is primarily based in downtown Toronto but will see some travel to various client sites at key project milestones.
- Bachelor’s degree in Computer Science, Engineering, Data Analytics, or related field.
- 4+ years of experience in data engineering or analytics engineering roles.
- Advanced Power BI skills including DAX and data modeling.
- Strong SQL and data transformation skills in Snowflake.
- Experience working with diverse data sources (ranging from PMIS tools like P6, EcoSys, etc. to SAP, SharePoint, etc.)
- Strong experience with data transformation for analytics and reporting.
- Hands-on expertise with Azure Data Factory (ADF) for orchestration and advanced ETL scenarios.
- Strong experience with Snowflake, including:
- SQL-based transformations
- Data modeling for analytics
- Performance tuning
- Experience preparing data for Power BI consumption.
- Advanced SQL skills and experience working with messy, inconsistent datasets.
- Experience working in Azure DevOps environments, including boards (work items), Repos, and CI/CD pipelines , to support analytics and data engineering delivery.
BONUS POINTS IF YOU HAVE:
- Domain Knowledge: Understanding of capital project controls, scheduling, or construction management.
- Certifications: SnowPro Core, Microsoft Power BI Data Analyst Associate (PL-300), and/or PMP/CSM.
- Ability to arrange priorities and escalate competing risks to meet deadlines.
- Keen eye for detail and adept problem-solving abilities.
- Must have demonstrated experience relaying and receiving information (written and verbal).
- Experience working with CI/CD pipelines, to support analytics and data engineering delivery.
- Effective skills in Microsoft Office.
- Equipped to work independently and as part of a team.
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, based on full-time employment, for roles that may be hired as set forth below.
The recruiting efforts for this position are intended to fill an existing position.
The base pay range shown below is intended as a guideline to reflect the majority of offers for this role. It does not represent a maximum limit — in some cases, actual compensation may exceed the range where appropriate.
Role Location Annual Salary Range
Toronto $118,000 to $145,000
