[Remote] Data Engineer
Note: The job is a remote job and is open to candidates in USA. Exodus Integrity Services is a staffing and consulting company seeking a Staff Data Engineer to join their engineering team in building modern data platforms. The role involves designing scalable data architectures, mentoring junior engineers, and driving data platform modernization with a focus on performance and security.
Responsibilities
- Define data architecture and platform strategy, leading design across pipelines, warehouses, and data lakes
- Build and optimize scalable data pipelines supporting batch and real-time processing
- Define and enforce data governance, quality standards, and compliance frameworks across the platform
- Build monitoring, logging, and alerting for data pipelines and services, and contribute to CI/CD workflows for data deployment and automation
- Drive data platform modernization, optimizing for performance, cost, and scalability
- Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace
- Design and implement data contracts and event flows in collaboration with backend, platform, and engineering teams
- Lead the design and implementation of data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
- Integrate data services with APIs, middleware, and third-party systems to support end-to-end data consumption
- Partner with leadership on data strategy, translating technical depth into decisions others can act on
- Collaborate closely with engineering, analytics, AI, and product teams to align data platforms with broader goals
- Advocate for data quality, governance, and platform best practices across teams and engagements
- Establish data engineering standards that lift the quality and consistency of work across the team
- Mentor junior and mid-level engineers, helping them grow their craft, confidence, and impact
- Make high-stakes architectural decisions with clear ownership and consideration of long-term tradeoffs
Skills
- 7+ years of professional data engineering experience, with experience leading complex data platform initiatives
- Strong system architecture background with expertise in distributed data systems
- Expert proficiency in Python, Scala, and SQL
- Deep expertise with cloud-native data platforms and enterprise data warehousing
- Strong expertise in data pipeline orchestration and processing
- Strong experience with streaming platforms and real-time data processing (e.g., Kafka, Kinesis, Pub/Sub)
- Strong data modeling expertise and experience with data transformation
- Strong experience with data quality, governance, and compliance frameworks
- Strong experience with container orchestration and CI/CD for data systems
- Strong experience building data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
- Demonstrated leadership and technical mentoring experience across a team or organization
- Strong stakeholder communication skills, with the ability to translate technical depth across audiences
- Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor
- Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment
- Experience with data mesh or data fabric concepts, lakehouse architectures, or governance framework implementation is a plus
Company Overview