Data Integration Eng

Description

At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong.

We are currently searching for a Data Integration Eng:

The Challenge (Responsibilities)

• 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.

Your Profile (Requirements)

• 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.
• 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.

Special Notes

• Client Position ID: AR 690985

Work Arrangement

We value flexibility to support your lifestyle. This position is available as:

• Remote.

If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page: https://www.sequoia-connect.com/careers/

Requirements

• 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.