Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, evaluate, implement, and sustain scalable ETL/ELT pipelines utilizing Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and associated services.

• Architect and oversee Azure-based data lake and data warehouse solutions, encompassing ADLS Gen2, Synapse, and Microsoft Fabric.

• Create and enhance dimensional, star-schema, normalized, and data-vault models tailored for business intelligence and AI/ML applications.

• Collaborate with AI Engineers to prepare and provide reliable data for model training, feature stores, retrieval-augmented generation, and inference pipelines.

• Integrate Azure OpenAI, Azure AI Foundry, Cognitive Services, embeddings, vector databases, and other AI services into data workflows and applications.

• Contribute to the data architecture for AI-driven applications utilized by both internal and external users.

• Establish and uphold controls for data quality, governance, lineage, access, security, and compliance.

• Monitor, diagnose, and enhance pipeline reliability, performance, and Azure cost efficiency.

• Convert business and product requirements into actionable technical data solutions in collaboration with Analytics, Product, Engineering, and other stakeholders.

• Offer technical guidance and mentorship to junior data engineers through code reviews, design discussions, and knowledge-sharing sessions.

• Assist in defining and enforcing data engineering standards, coding conventions, reusable patterns, and best practices.

• Support scoping and estimating data engineering tasks for sprint planning and project roadmaps.

⛳️ Requirements

• 4-6 years of experience as a Data Engineer or in a similar data infrastructure role.

• Extensive hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake Storage Gen2.

• Proficiency in SQL and at least one programming language; Python is preferred.

• Experience in building and orchestrating scalable ETL/ELT pipelines.

• Familiarity with data modeling principles, including star schema, normalization, and data vault.

• Experience in supporting model training, feature stores, inference pipelines, or related AI/ML data workflows.

• Knowledge of Azure OpenAI Service or similar LLM integration patterns, including RAG pipelines, embeddings, and vector databases.

• Experience with Git, CI/CD, testing, and deployment practices.

• Understanding of data security, compliance, governance, quality, and lineage principles.

• Experience mentoring engineers, leading small technical initiatives, or acting as a technical point of contact.

• Formal people-management experience is not necessary.

🏝️ Benefits

• Supportive, collaborative environment.

• Work-life balance.

• Professional development opportunities.

• Technical and personal advancement opportunities.

• Distributed workplace / remote work arrangement.