Senior Data Engineering & AI Platform Engineer (Contract-to-Hire)

Job Description Senior Data Engineering & AI Platform Engineer (Contract-to-Hire)

Key Responsibilities

• Design, build, and operate scalable data engineering platforms using modern ETL/ELT frameworks, including Azure Data Factory, Delta Lake, and cloud-native pipelines.
• Architect modular, reusable data systems supporting batch and streaming workloads, advanced analytics, and AI/ML use cases.
• Influence enterprise data and AI platform architecture, including lakehouse design, metadata management, and data quality frameworks.
• Develop and optimize PL/SQL, Python, and Unix-based data processing solutions for high-volume, low-latency data pipelines.
• Enable Generative AI use cases by designing structured and unstructured data pipelines supporting NLP, prompt engineering, vectorization, RAG, and inference workflows.
• Drive code reusability and standardized engineering patterns through shared frameworks, libraries, and best practices.
• Implement mature DevOps and DataOps practices, including CI/CD, automated testing, monitoring, incident management, and cloud cost optimization.
• Analyze complex business and data challenges, translating them into scalable engineering and AI solutions that deliver measurable business value.
• Lead adoption of best practices in data modeling, security, governance, and regulatory compliance.
• Modernize existing data platforms to improve performance, scalability, reliability, and AI readiness.
• Collaborate with business, analytics, data science, and product teams in an Agile environment to deliver high-impact solutions.
• Mentor engineers on cloud, data engineering, and Generative AI technologies while promoting engineering excellence.
• Support technical hiring, interview processes, and capability development across teams.
• Communicate technical solutions effectively to both technical and business stakeholders through presentations, demos, and architecture discussions.

Required Skills

• Strong experience in Data Engineering and modern cloud data platforms.
• Hands-on expertise with Azure Data Factory, Delta Lake, Azure Data Lake, and cloud-native data pipelines.
• Strong programming skills in Python, PL/SQL, SQL, and Unix Shell Scripting.
• Experience building scalable ETL/ELT pipelines for large-scale enterprise data platforms.
• Knowledge of streaming technologies and lakehouse architecture.
• Experience with DevOps/DataOps practices, CI/CD pipelines, monitoring, and automated testing.
• Good understanding of data governance, metadata management, security, and data quality frameworks.
• Exposure to Generative AI, vector databases, embeddings, RAG architectures, LLM integrations, or AI-enabled data platforms is highly preferred.
• Strong communication, stakeholder management, and mentoring skills.

Contract-to-Hire Details

Initial engagement will be on a 1-year contractual basis.

Based on individual performance, business requirements, and client evaluation, there is an opportunity to be converted to a permanent role