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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 #LI_REMOTE

Data Engineer - Manager

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Data Engineer - Manager

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