Data Engineering, Management, & Governance Specialist - Finance

Accenture•St. Louis, MO

4d•$54,400 - $205,800

About The Position

As a Data Engineering, Management & Governance professional at Accenture, you will build data solutions for ingesting, transforming, and structuring data using vendor and open-source tools to build, migrate, and deploy data pipelines. The role applies data engineering, cloud architecture, and DevOps principles to create scalable, reusable data workflows and support data governance and quality. Travel may be required, ranging from 0% to 100% depending on business need and client requirements. Compensation varies by location, role, skills, and experience. The listed annual salary ranges are: California $70,350–$205,800; Colorado, Connecticut, Maryland, Minnesota $63,800–$177,800; District of Columbia and New Jersey $68,000–$189,300 and $68,000–$205,800, respectively; Illinois $59,100–$177,800; Maine $54,400–$151,400; Massachusetts $63,800–$189,300; New York $66,300–$205,800; Ohio $59,100–$164,600; Virginia $59,100–$189,300; and Washington $80,200–$189,300. The posting is anticipated to remain open until 12/31/2026.

Requirements

At least 3 years of hands-on experience with cloud and big data technologies, such as serverless data processing, Spark/SparkSQL, batch and streaming services, event-driven data pipelines, cloud databases, and programming languages such as Python, SQL, and Node.js.
At least 3 years of experience with cloud data storage, data management, and data services.
At least 3 years of experience with data supply chains, including streaming pipelines to address acquiring data, evaluating its value, distilling it, and analyzing it.
At least 3 years of experience examining data from multiple sources and sharing insights that provide competitive advantage.
At least 2 years of experience with DevOps and CI/CD processes.
At least 2 years of experience with scheduling and orchestration.
Bachelor’s degree or equivalent (minimum 12 years) work experience; applicants with an associate’s degree must have at least 6 years of work experience.
Applicants for US employment must have work authorization that does not now or in the future require visa sponsorship.

Nice To Haves

Experience in large-scale data integration and data warehouse solutions.
Ability to lead and facilitate design sessions with business customers and the BI team to derive data requirements and data design information.
Cloud data-path certifications, such as AWS.
Business acumen and domain knowledge, such as Finance, Supply Chain, or Sales, to understand data nuances, collaborate across functions, and communicate with leadership teams.
Understanding of governance and security best practices and organizational policies, procedures, and protocols for regulatory and privacy compliance.
Basic knowledge of machine learning, models, and statistical analysis to collaborate with data scientists and business leaders.
Demonstrable knowledge of artificial intelligence, machine learning, data science, and other relevant technical domains.

Responsibilities

Apply data engineering principles to create reusable workflows for data ingestion, quality assurance, transformation, and optimization.
Design, build, and test scalable data pipelines using extract, transform, and load tools, validating outputs against source totals such as financial balances and transaction counts.
Document requirements and technical design documents.
Deploy solutions to production environments using CI/CD DevOps and cloud architecture principles.
Migrate data from legacy data warehouses using cloud architecture principles.
Automate the flow of data for consumption.
Build business processes that enable data governance, including stewardship of financial, customer, or product master data.
Design and advise on data quality rules and establish effective data compliance policies.