数据集成工程师
Data Integration Eng
描述
在Sequoia Connect，我们是一个以人才为核心的科技生态系统，重新定义精英专业人士与全球数字环境的互动方式。我们超越传统模式，成为全球顶尖1%人才的催化剂，将人类潜力与复杂的工业执行相结合。加入我们的核心团队，你不仅仅是获得一个职位；而是与一个致力于更新你的“人类操作系统”并通过对世界级高影响力项目的推进加速你成长的战略合作伙伴携手同行。
我们目前正在与一家快速发展的、以自动化为主导的巨头公司合作，为金融、医疗保健和制造行业的31家财富500强企业提供服务。该公司拥有超过32,000名员工，业务遍及28个国家，是数字化转型的巨擘。他们的“一切自动化，一切云化”战略确保你将在人工智能驱动的自动化和云解决方案的最前沿工作。
这是你在“客户成功，始终如一”的环境中茁壮成长的机会，这里重视持续学习和彻底的自主权。你将在一个覆盖全球39个交付中心的国际专家网络中协作，接触到重新定义行业标准的复杂工程挑战。如果你是一位追求动态、前瞻性工作环境的有抱负的专业人士，你的成长是首要任务，那么这里就是你的归属地。
我们正在寻找一名数据集成工程师：
挑战（职责）
- 为Microsoft Fabric、Snowflake、Databricks、Azure Synapse、BigQuery和类似平台设计和实现可重用的云数据连接器和提取模式。
- 构建直接平台连接的数据工作流、客户数据仓库副本、镜像或复制的ERP数据库以及结构化或非结构化文档来源。
- 开发独立于ERP的数据仓库和数据库镜像蓝图，包含标准配置、验证、治理和操作控制。
- 评估原生平台连接器，并通过标准API、事件和配置合同将其与我们客户的云连接套件集成。
- 实现包括模式捕获、行数对账、源和目标验证、可重启性、异常处理和执行可追溯性的提取控制。
- 开发增量提取、变更数据捕获、分区和并行处理的可扩展模式。
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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:
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.
Originally posted on Himalayas