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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer and Analyst - Hybrid - **Company:** Genesis10 - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Salary:** $174,845.0 - $191,485.0 - **Contract:** Temporary contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Data Analysis, Application Release Automation, Microsoft Azure, Big Data, Cloud Computing, Code Review, Continuous Integration, Data as a Services, Data Deduplication, Information Engineering, Relational Databases, JSON, Python (Programming Language), Machine Learning, Microsoft SQL Server, Modular Design, MongoDB, OpenShift, Parsing, Performance Tuning, Systems Development Life Cycle, SQL Databases, Data Streaming, Test Case, Extensible Markup Language (XML), Parquet, Google Cloud, Feature Engineering, Sql Optimization, Large Language Models, Git, Pandas, Containerization, Data Lakes, Pyspark, Semi-structured Data, Kubernetes, Apache Kafka, Feature Extraction, GPT, Data Pipelines, Docker - **Published:** August 25, 2026 - **Apply:** https://www.dice.com/job-detail/adb8430b-f41e-49c9-9845-6ac77e7a43fe ## About the Role * 5-10+ years of combined data engineering/analysis experience * Expert Python skills for data engineering & analysis (pandas, PySpark or similar, modular design, testing) * Advanced SQL skills (analytical window functions, performance optimization, CTEs, partitioning, large-scale joins) * Java experience for service implementations (APIs, data services, utilities), with strong SDLC discipline * Proven experience with large datasets: profiling, cleaning, deduping, and synthesizing insights; comfort with semi-structured data (XML/JSON) * Experience with data lake / warehouse concepts (e.g., parquet, object storage, lakehouse patterns) * Hands-on CI/CD (Git, pipelines, build/test/release automation) and containerized deployments (Docker/Kubernetes; OpenShift/OCP highly preferred) * Independent problem solver with the ability to break down ambiguous data issues, form hypotheses, validate with code, and communicate outcomes clearly * Practical GenAI usage: ability to craft prompts and evaluate LLM outputs for data triage, test case generation, and analysis acceleration * Foundational ML knowledge: familiarity with applying models/techniques relevant to data quality (e.g., clustering, similarity, dedup/record linkage, anomaly detection) Desired skills: * Payments domain experience (especially wire payments) * Experience with streaming (Kafka), workflow/orchestration (Airflow), and feature engineering for ML * Familiarity with Microsoft SQL Server or similar enterprise RDBMS * Cloud platform experience (Google Cloud Platform, AWS, Azure) * MongoDB experience ## Description We are hiring a hands-on Senior Data Engineer and Analyst who can both build data pipelines and analyze large datasets. You will design and deliver scalable services in Python and Java on Red Hat OpenShift (OCP) and cloud platforms. This role involves operating within agile backlogs, independently breaking down complex data problems, and serving as a technical leader for SQL, Python, data modeling, ML application, and practical GenAI use., * Own full-cycle data problem solving: profile large datasets, design pipelines, engineer transformations, and perform deep analysis to identify patterns, outliers, and root causes * Implement production-grade code: develop data services and utilities in Python (primary) and Java (for service implementations) with strong testing, observability, and reliability * Write advanced SQL for data exploration, deduplication, quality checks, and performance-tuned analytics across data lakes/warehouses * Parse, normalize, and analyze XML payment objects to identify unique examples, apply deduplication strategies, and generate representative test cases * Apply LLM-powered techniques (Gemini/GPT) to accelerate data triage, test generation, and anomaly detection with careful evaluation and guardrails * Apply machine learning knowledge (e.g., feature extraction, similarity measures, dedup/record-linkage techniques) to large-scale data problems * Set engineering standards for architecture, SDLC excellence, CI/CD automation, and code review quality ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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