About PeopleCaddie
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
11 - 50 Employees
Headquarters location
Rosemont, IL, US
Year founded
2016
$60 - $85/hr
Other
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Job description
Job Description:
Job Title: Data Engineer - Manager
Company: Large Public Accounting Firm
Location: Remote
Duration: 5+ Months
Pay Rate: $60-$85 per hour (C2C), depending on experience
Role Overview
The Data Engineer - Manager plays a critical role in advancing a modern, enterprise-wide data strategy focused on enabling data-driven decision-making, advanced analytics, and AI-powered insights. This role supports a centralized Data & Analytics function aligned to core technology pillars including Application Modernization, AI, and Data.
You will be responsible for designing, building, optimizing, and maintaining scalable data platforms and pipelines that support analytics, reporting, AI/ML, and operational intelligence across the organization. This is a senior, hands-on engineering role requiring deep technical expertise, strong collaboration skills, and the ability to translate complex data challenges into reliable, high-value solutions.
Key Responsibilities
Design, develop, and maintain scalable and resilient data pipelines for ingesting, transforming, and delivering data from diverse internal and external sources. Integrate data across databases, data warehouses, APIs, and third-party platforms while ensuring data accuracy, consistency, and integrity. Apply data cleansing, validation, aggregation, enrichment, and transformation techniques to prepare analytics-ready datasets. Optimize data pipelines and processing workflows for performance, scalability, reliability, and cost efficiency. Monitor and tune data systems; identify performance bottlenecks and implement indexing, caching, and optimization strategies. Embed data quality checks, validation rules, and governance controls directly within data pipelines. Collaborate with architects, data scientists, AI engineers, and analysts to support advanced analytics, business intelligence, and AI/ML use cases. Take ownership and accountability for maximizing the value of enterprise data assets used for insights, automation, and decision support. Clearly communicate complex technical concepts to both technical and non-technical stakeholders, including senior leadership. Demonstrate critical and creative thinking by using diverse research tools and analytical processes to interpret complex data, identify trends and opportunities, and make timely decisions that balance short- and long-term impacts, while advising and influencing key decision makers through persuasive negotiation. Proactively drive business and client success by taking initiative, anticipating needs and helping others think ahead, embracing challenges beyond your comfort zone, thinking and acting strategically, and continuously innovating and sharing ideas to improve processes and efficiency. Demonstrate flexibility and responsiveness by effectively navigating diverse and unexpected situations, prioritizing multiple work streams, and balancing short- and long-term objectives to achieve goals. Exhibit humility, empathy, and self-awareness by valuing individual differences, treating everyone with respect and kindness, actively listening with genuine curiosity to diverse perspectives, and taking ownership of how your emotions and actions affect others. Model integrity and optimism by aligning actions with words, assuming positive intent, staying composed and resilient under pressure, and handling conflict and difficult conversations constructively. Cultivate a strong personal brand that differentiates you with internal and external stakeholders by proactively sharing knowledge, leveraging your talents, and delivering visible impact.
Required Experience & Qualifications
Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related quantitative field. 8+ years of experience in data engineering, including: Strong programming experience with Python, SQL, Java, and/or C#. Hands-on Experience With Modern Data Platforms And Tools, Including Data modeling and architecture ETL / ELT and data integration Data warehousing and analytics platforms Data quality, master data management, and governance Business intelligence and advanced analytics (predictive and prescriptive) Microsoft Azure technologies (SQL Server IaaS/PaaS, Synapse, Cosmos DB, Azure Data Factory, Databricks, HDInsight, Fabric, Power BI) Informatica Cloud (CIH, DIH, CDGC, Master Data Management, Data Quality) Snowflake and other leading cloud data technologies
Desirable Characteristics
Certifications in relevant technologies listed above Previous experience in the professional services or accounting industry Previous client service or consultative experience Previous experience working in a managed service provider environment
Job Title: Data Engineer - Manager
Company: Large Public Accounting Firm
Location: Remote
Duration: 5+ Months
Pay Rate: $60-$85 per hour (C2C), depending on experience
Role Overview
The Data Engineer - Manager plays a critical role in advancing a modern, enterprise-wide data strategy focused on enabling data-driven decision-making, advanced analytics, and AI-powered insights. This role supports a centralized Data & Analytics function aligned to core technology pillars including Application Modernization, AI, and Data.
You will be responsible for designing, building, optimizing, and maintaining scalable data platforms and pipelines that support analytics, reporting, AI/ML, and operational intelligence across the organization. This is a senior, hands-on engineering role requiring deep technical expertise, strong collaboration skills, and the ability to translate complex data challenges into reliable, high-value solutions.
Key Responsibilities
Required Experience & Qualifications
Desirable Characteristics
peoplecaddie.com
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Software Engineer?
A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.
Q: What is the career path for a Data Software Engineer?
A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.