PeopleCaddie

Data Engineer - Manager

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Senior Data Engineer - Manager for a 6-12 month contract, fully remote, paying $80–$85/hour. Requires 8+ years of data engineering experience, strong skills in Python, SQL, Azure technologies, and expertise in data modeling, ETL, and data governance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
680
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🗓️ - Date
June 17, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Chicago, IL
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🧠 - Skills detailed
#Data Management #C# #Scala #ML (Machine Learning) #Computer Science #Data Modeling #SQL (Structured Query Language) #Data Warehouse #Informatica #AI (Artificial Intelligence) #Azure #Azure Data Factory #SQL Server #Data Strategy #Python #Data Cleansing #Strategy #Informatica Cloud #Data Quality #Snowflake #Data Accuracy #MDM (Master Data Management) #Java #BI (Business Intelligence) #Leadership #Databricks #Data Engineering #Data Science #Datasets #Data Integration #Databases #"ETL (Extract #Transform #Load)" #Indexing #Microsoft Power BI #Cloud #Data Pipeline #Automation #Programming #Microsoft Azure #ADF (Azure Data Factory) #Synapse
Role description
Job Description Title: Senior Data Engineer – Contract Client: Large Public Accounting Firm Engagement: 6-12 Months+ Contract Work Model: Fully Remote Rate: $80–$85/hour (C2C) Role Overview The Senior Data Engineer 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. 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: • 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) Strong programming experience with Python, SQL, Java, and/or C#. Hands-on Experience With Modern Data Platforms And Tools, Including • 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 #PCIT