Data and Integration Engineer

Responsibilities

• Data Management & Data Understanding
• Manage structured, semi-structured, and unstructured data used across digital product platforms.
• Analyze source data formats including SQL tables, JSON, XML, CSV, documents, logs, images, geospatial files, and API payloads.
• Define data mapping, metadata, lineage, validation rules, and data quality expectations.
• Support reporting, analytics, operational dashboards, product insights, and downstream data requirements.
• Data Ingestion, Validation & Processing
• Design and support batch, scheduled, and near-real-time data ingestion workflows from internal and external sources.
• Build validation, reconciliation, deduplication, enrichment, transformation, and error-handling routines.
• Support ETL/ELT processes, file processing, document ingestion, API-based data exchange, and cloud data movement.
• Monitor ingestion health, failed loads, schema changes, data anomalies, and data completeness.
• Integration Engineering
• Build and maintain APIs, connectors, integration jobs, scripts, and service-based data exchange workflows.
• Integrate product platforms with enterprise systems, external providers, GIS/geospatial platforms, identity services, and data stores.
• Support event-driven, API-based, file-based, and scheduled integration models based on product needs.
• Work with architects and developers to define integration contracts, error handling, retry logic, monitoring, and operational support requirements.
• Data Quality, Support & Governance
• Define and maintain data quality checks, reconciliation reports, validation dashboards, and exception-handling processes.
• Participate in root-cause analysis of data defects, integration failures, ingestion errors, and downstream inconsistencies.
• Support migration, onboarding, configuration, and release activities involving data and integrations.
• Maintain documentation for data flows, integration dependencies, transformation logic, and support procedures.