Data Operations Engineer

What We're Looking For

• Strong experience designing and operating data pipelines with defined latency, freshness, and accuracy SLAs
• Expert SQL skills and proven ability to work with large, complex datasets across diverse partner schemas
• Hands-on experience with modern data tooling such as Snowflake, dbt, Airflow, and schema registries
• PRACTICAL, IN-THE-WORKFLOW USE OF AGENTIC TOOLING TO ACCELERATE SCHEMA MAPPING, ANOMALY DETECTION, DATA PROFILING, AND PIPELINE DEBUGGING
• Track record of building monitoring, alerting, runbooks, and reconciliation processes for systems with external commitments
• Ability to ramp quickly on new partner ecosystems, data formats, and domains
• PROVEN SUCCESS LEADING WORK IN AMBIGUOUS, FAST-MOVING ENVIRONMENTS
• EXCELLENT COLLABORATION, COMMUNICATION, AND CROSS-TEAM INFLUENCE

Problem Solving & Overcoming Obstacles

• Evaluate trade-offs across freshness, accuracy, latency, and cost, especially in partner-driven and AI-augmented data workflows
• Simplify pipelines and drive down data debt while supporting rapid experimentation and onboarding of new partners
• Owning ambiguous data challenges — mismatched schemas, silent failures, partial loads, reconciliation gaps — and drive them to resolution
• Apply strong diagnostics to identify root causes of data discrepancies and deliver resilient, auditable solutions

Mentorship & Growth

• Mentor engineers and analytics contributors through coaching and feedback, including adoption of modern and AI-augmented data practices
• SUPPORT TEAM GROWTH BY PROMOTING CONTINUOUS LEARNING, EXPERIMENTATION, AND ADAPTABILITY IN DATA ENGINEERING METHODS
• FOSTER A CULTURE OF PSYCHOLOGICAL SAFETY, COLLABORATION, AND SHARED OWNERSHIP OF DATA QUALITY
• HELP RAISE THE BAR IN HIRING, ENSURING ALIGNMENT WITH DATASITE'S TECHNICAL AND CULTURAL EXPECTATIONS

Ownership & Accountability

• OWN END-TO-END DESIGN AND DELIVERY OF INGESTION PIPELINES, TRANSFORMATION LAYERS, RECONCILIATION PROCESSES, AND PARTNER-FACING DATA PRODUCTS
• BUILD PIPELINES WITH STRONG OBSERVABILITY, ALERTING, AND SELF-HEALING CHARACTERISTICS — SO ISSUES ARE IDENTIFIED AND, WHERE POSSIBLE, REMEDIATED BEFORE THEY BECOME PARTNER-VISIBLE
• TRACK PROGRESS, MANAGE RISK, AND ADAPT PLANS WHILE MAINTAINING A BIASED FOR ACTION AND HIGH-QUALITY EXECUTION
• SURE NEW PARTNERSHIPS ARE DELIVERED WITH CARE, RELIABILITY, AND INGENUITY, BALANCING SPEED WITH LONG-TERM DATA INTEGRITY

How We Work Together

• Strategic Data Leadership
• Guide data architecture decisions that incorporate AI-augmented capabilities into ingestion, transformation, and reconciliation workflows for partner integrations
• Partner with Product, Engineering, and partner teams to develop flexible data roadmaps aligned to Datasite strategy while adapting to fast-evolving partner data needs
• Drive pipeline improvements that scale across diverse partner data formats, reduce operational overhead, and improve reliability of SLA-bound data products
• Maintain adaptable data contracts and schema strategies, enabling rapid onboarding of new partners in uncertain, high-velocity environments
• Cross-Team Collaboration & Influence
• Identify and drive cross-platform improvements (schema registries, validation tooling, data contracts, lineage tracking) that enhance partner and developer experiences
• Collaborate across Engineering, Product, and partner teams to deliver AI-first, integration-ready data solutions
• Communicate complex data concepts clearly, translating pipeline design trade-offs and SLA commitments for diverse stakeholders
• Provide technical guidance that ensures alignment, simplicity, and consistency across data flows and partner integrations