Data Engineer

Data Engineer – Full Stack – Python, AI/ML Location: Remote – US Duration: 6 Months (possibility of renewal or contract-to-hire thereafter) Rate: $50–60/hour w2Join a remote, US-based opportunity supporting a data governance-focused engineering team as a hands-on Data Engineer working across full-stack data engineering and AI/ML-enabled workflows. This role is ideal for a mid-level engineer with experience in Python, SQL, Spark/PySpark, and Airflow, contributing to initiatives involving data quality, lineage, metadata, master data management, and analytics-ready datasets. This is a contract opportunity with the potential for renewal or conversion to a full-time position.This opportunity offers the chance to work at the intersection of modern data engineering and emerging AI/ML-powered governance practices. You will contribute to initiatives such as embedding-based data classification, anomaly detection, LLM-assisted catalog search, and governed data exposure for AI assistants while partnering with technical teams and stakeholders in a collaborative environment. If you enjoy solving complex data problems, building scalable pipelines, and expanding your expertise in data governance and AI, this role provides strong technical growth potential.Contract Duration: 6 Months (possible extensions)Required Skills & Experience· Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or related field· 2+ years of experience building data pipelines using Python (Pandas, NumPy, SciPy) and SQL· Experience with Apache Spark or PySpark and workflow orchestration tools such as Apache Airflow· Experience designing schemas across relational and analytical databases including PostgreSQL, MySQL, and SQL Server· Experience implementing data quality validation, exploratory data analysis (EDA), and integrity enforcement in production datasets· Hands-on experience with at least one cloud platform (AWS, Azure, or GCP)· Working familiarity with Python ML libraries such as Scikit-Learn for feature engineering and exploratory analysis· Experience producing analytics-ready datasets for BI platforms including Tableau, Power BI, or Looker· Experience with Git, code reviews, CI/CD practices, and modular engineering workflows· Strong written and verbal communication skills with collaborative working styleDesired Skills & Experience· Exposure to data governance tooling including metadata management, data lineage, stewardship workflows, and catalogs· Experience with MDM platforms, especially Informatica MDM SaaS, C360, or multi-domain environments· Experience supporting compliance, audit, or regulated-data initiatives· Experience with Apache Kafka and Spark Structured Streaming· Exposure to lakehouse technologies including Delta Lake and Databricks· Familiarity with LLM APIs, RAG architectures, agentic AI patterns, and MCP applied to governance use cases· NLP and text preprocessing experience for unstructured data· Power BI certifications· Attention to detail and ownership of data quality outcomes· Collaborative, team-first mindset with the ability to operate within established engineering standards· Clear written and verbal communication skills with technical and non-technical audiences· Curiosity and willingness to grow within modern AI/ML-assisted governance environmentsWhat You Will Be DoingTech Breakdown· 40% Python, SQL, and Data Pipeline Engineering· 20% Spark/PySpark, Airflow, and Workflow Automation· 20% Data Governance, Quality, Metadata, and Lineage· 10% AI/ML-Assisted Governance and Analytics· 10% BI Reporting and Cloud-Based Data PlatformsDaily Responsibilities· 80% Hands On· 0% Management Duties· 20% Team Collaboration