Senior Software Engineer

Genesis10•Iselin, NJ

3d•Hybrid

About The Position

Genesis10 is seeking a hands-on Senior Data Engineer and Analyst for a contract position with a Global Financial Institution. This role involves designing and delivering scalable services in Python and Java on Red Hat OpenShift (OCP) and cloud platforms. The position operates within agile backlogs, requiring independent breakdown of complex data problems, and serving as a technical leader for SQL, Python, data modeling, ML application, and practical GenAI use. The role is for 18+ months and is hybrid.

Requirements

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)

Nice To Haves

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 (GCP, AWS, Azure)
MongoDB experience

Responsibilities

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