[Hiring] Data Integration Engineer @Sequoia Connect

Role Description

We are currently searching for a Data Integration Engineer:

• Design and implement reusable cloud data connectors and extraction patterns for Microsoft Fabric, Snowflake, Databricks, Azure Synapse, BigQuery and comparable platforms.
• Build data workflows for direct platform connections, client data warehouse copies, mirrored or replicated ERP databases, and structured or unstructured document sources.
• Develop the ERP-independent data warehouse and database-mirroring blueprint with standard configuration, validation, governance and operational controls.
• Evaluate native platform connectors and integrate them with Our Client's Cloud Connector Suite through standard APIs, events and configuration contracts.
• Implement extraction controls including schema capture, row-count reconciliation, source and destination validation, restartability, exception handling and execution traceability.
• Develop scalable patterns for incremental extraction, change data capture, partitioning, parallel processing, pagination and high-volume data movement.
• Capture and preserve extraction parameters, schemas, selected objects, run history, technical metadata and evidence required for auditability.
• Create automated integration, data-quality, performance, volume, resilience and security tests.
• Produce implementation guides, configuration references, technical design documents, operational runbooks and connector-development documentation.

Qualifications

• 5+ years of relevant data engineering or integration experience.
• Strong hands-on experience with at least two modern data platforms such as Microsoft Fabric, Azure Data Factory, Databricks, Snowflake, Azure Synapse Analytics.
• Proficiency in SQL and one or more development languages such as Python, C#, Java, Scala or TypeScript.
• Experience developing data pipelines, reusable connectors, integration APIs or enterprise ingestion frameworks.
• Good knowledge of relational databases, data warehouses, lakehouses, object storage and enterprise data formats.
• Experience with REST APIs, JDBC/ODBC connectivity, file-based interfaces and cloud-native connector frameworks.
• Experience with incremental loads, change data capture, partitioning, batching, pagination, retries, resumability and performance optimisation.
• Ability to capture schemas, metadata, lineage, run information, data-quality outcomes and source-to-target reconciliation evidence.
• Knowledge of secure network and identity patterns including private endpoints, firewall controls, managed identities, service principals and encrypted transport.
• Experience with CI/CD, source control, automated testing and Infrastructure as Code.
• Strong troubleshooting capability across data, authentication, connectivity, connector and platform-performance issues.

Requirements

• High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
• Technologist DNA: A deep understanding of the difference between "coding" and "engineering."

Desired

• Experience with Microsoft Graph and SharePoint APIs for secure document or invoice retrieval.
• Knowledge of database replication, mirroring, read replicas, change data capture or log-based extraction.
• Familiarity with Delta Lake, Apache Spark, Parquet, JSON, CSV and XML.
• Experience with ERP-derived financial data such as general ledger, subledger, master and transactional datasets.
• Understanding of auditability, evidence generation, source-to-target reconciliation and data lineage.
• Experience assessing vendor-native connectors through structured proofs of concept.
• Microsoft Fabric, Azure Data Engineer, Databricks or Snowflake certification.
• Familiarity with cloud-native foundations or AI coding assistants.

Languages

• Advanced Oral English: For seamless collaboration with global teams.
• Advanced Spanish.

Work Arrangement

• Remote.