Brightfield - Senior Data Integration Engineer
Requirements
• 5+ years of experience in data engineering, data integration, or backend software engineering, with a strong focus on building production data pipelines. • Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience. • Expert-level proficiency in Python and SQL, with deep experience transforming and working with large, complex datasets (structured and unstructured). • Hands-on experience implementing customer workflows through REST APIs, including working with JSON data formats. • Strong experience working with AWS and other cloud platforms and modern data warehouses (e.g., Snowflake). • Solid understanding of data modeling, ETL/ELT best practices, and data quality management. • Proven ability to troubleshoot complex data and integration issues across distributed systems. • Comfort working in a remote-first, highly collaborative environment with distributed teams. • Experience integrating enterprise or customer data at scale, particularly in analytics, SaaS, or data platform environments. • Familiarity with event-driven architectures, message queues, or streaming technologies. • Experience supporting AI, analytics, or machine learning workflows through reliable data pipelines. • Knowledgeable in using AI to build and deploy data solutions. • Prior experience mentoring or leading technical initiatives across teams.
Responsibilities
• Develop and manage integrations between internal systems, customer environments, SaaS platforms, and data warehouses using APIs and workflow orchestration tools. • Analyze customer’s workflows and data sources to integrate, ingest and unify customer’s data and onboard to TDX platform. • Implement TDX APIs with customer and partner solutions. • Support Brightfield’s existing taxonomy and data processes, models, mappings, and transformation logic to support consistent, high-quality data output across the Brightfield platform. • Optimize data pipelines for performance, scalability, resiliency, monitoring, and data quality. • Ensure data integrity, security, and compliance by implementing validation, access controls, and governance best practices. • Collaborate cross-functionally with Product, Data Science, Analytics, and Customer-facing teams to translate customer’s business and product requirements into technical solutions. • Contribute to continuous improvement of Brightfield’s data analysis, infrastructure, tooling, and best practices.
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