Senior Data Engineer

As a Senior Data Engineer, you will design, build, and operate the data pipelines and APIs that support our data-driven and AI-enabled products. You will own how data moves from ingestion through consumption, ensuring it is reliable, secure, and available for the teams and products that depend on it.

You will partner with product, analytics, data science, and machine learning teams to translate business needs into scalable production solutions. This hands-on role also includes leading technical reviews, establishing engineering standards, and mentoring other engineers., * Design, build, and maintain batch and streaming pipelines for structured and unstructured data from databases, APIs, event streams, and files.

• Develop ETL/ELT processes and optimize performance, cost, scalability, and reliability.
• Build and operate cloud solutions using AWS services such as EC2, ECS, Lambda, API Gateway, and SQS.
• Develop and manage data workflows, including scheduling, dependencies, retries, alerts, and backfills.
• Establish monitoring, logging, and observability to identify issues and support reliable production operations.
• Design, develop, test, and maintain secure REST APIs and Python-based data services using frameworks such as FastAPI or Flask.
• Implement API authentication, authorization, validation, versioning, error handling, rate limiting, and documentation.
• Build data foundations for machine learning and generative AI, including feature pipelines, training and inference datasets, embeddings, and retrieval-based solutions.
• Integrate AI tools and large language model (LLM) APIs into workflows for document processing, enrichment, classification, and summarization.
• Implement data quality checks, validation, lineage, and documentation, applying security, privacy, and compliance standards.
• Lead architecture and code reviews, mentor engineers, and communicate technical recommendations to business and technical stakeholders.

• 8-10 years of professional experience in data engineering or a related field.
• Strong Python and advanced SQL skills, with experience delivering production data pipelines at scale.
• Hands-on experience with at least one workflow orchestration platform and big data processing frameworks.
• Experience developing and deploying production REST APIs, including integration, security, and automated testing.
• Experience with cloud platforms and data services.
• Understanding of data warehousing, lakehouse architecture, and data modeling.
• Working knowledge of AI and machine learning workflows, LLM APIs, embeddings, and vector databases.
• Experience with Git, CI/CD, Docker, and infrastructure as code tools such as Terraform.
• Strong problem-solving, communication, and stakeholder management skills., * Experience building and operating solutions on AWS.
• Experience delivering retrieval-augmented generation (RAG) or agent-based solutions in production.
• Knowledge of data governance, cataloging, and lineage tools.
• Cloud or data platform certifications.
• Healthcare industry experience.
• Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.