Data Engineering, Management, & Governance Specialist - Finance

Accenture•Chicago, IL

About The Position

Accenture is hiring a Data Engineering, Management & Governance Specialist to build data solutions for ingesting, transforming, and structuring data. The role uses vendor and open-source tools to build, migrate, and deploy data pipelines, and applies cloud architecture, DevOps, and data governance practices. It supports financial data use cases and may require travel ranging from 0% to 100%, depending on business needs and client requirements.

Requirements

At least 3 years of hands-on experience with cloud and big data technologies, including 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, and addressing data acquisition, evaluation, distillation, and analysis challenges.
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, with a minimum of 12 years of work experience; alternatively, an associate’s degree with a minimum of 6 years of work experience.

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 design information.
Cloud data path certifications, such as AWS.
Business acumen and domain knowledge in areas such as Finance, Supply Chain, or Sales, including the ability to recognize nuances in data meaning, 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.
Travel as required by business needs and client requirements; travel may range from 0% to 100%.