(Services) Data Engineer

<p>As a Data Engineer<br>You design, build, and optimize large-scale data pipelines and platforms across cloud environments. You manage data integration from multiple business systems, ensuring high data quality, performance, and governance. You collaborate with cross-functional teams to deliver trusted, scalable, and secure data solutions that enable analytics, reporting, and decision-making.</p> <p>Meet the job</p> <p>● <strong data-stringify-type="bold">Data Engineering</strong>: Design, build, and optimize scalable ETL/ELT pipelines using Azure Data Factory, Databricks, PySpark, and SQL;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Cloud Data Platforms</strong>: Manage and integrate data across Azure (Synapse, Data Lake, Event Hub, Key Vault) and GCP (BigQuery, Cloud Storage);<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">API Integration</strong>: Develop workflows for data ingestion and processing via REST APIs and web services, including integrations with BambooHR, Salesforce, and Oracle NetSuite;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Data Modeling &amp; Warehousing</strong>: Build and maintain data models, warehouses, and lakehouse structures to support analytics and reporting needs;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Performance Optimization</strong>: Optimize Spark jobs, SQL queries, and pipeline execution for scalability, performance, and cost-efficiency;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Governance &amp; Security</strong>: Ensure data privacy, security, and compliance while maintaining data lineage and cataloging practices;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Collaboration</strong>: Partner with business stakeholders, analysts, and PMO teams to deliver reliable data for reporting and operations;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Documentation</strong>: Create and maintain technical documentation for data processes, integrations, and pipeline workflows;<br><br>How about you</p> <p>● <strong data-stringify-type="bold">Education</strong>: Bachelor’s/Master’s degree in Computer Science, Engineering, Analytics, Mathematics, Statistics, IT, or equivalent;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Experience</strong>: 5+ years of experience in Data Engineering and large-scale data migration projects;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Technical Skills</strong>: Proficient in SQL, Python, and PySpark for data processing and transformation;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Big Data &amp; Cloud</strong>: Hands-on expertise with Apache Spark, Databricks, and Azure Data Services (ADF, Synapse, Data Lake, Event Hub, Key Vault);<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">GCP Knowledge</strong>: Exposure to Google Cloud Platform (BigQuery, Cloud Storage) and multi-cloud data workflows;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Integration Tools</strong>: Exposure to tools such as Workato for API-based data ingestion and automation;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Best Practices</strong>: Strong understanding of ETL/ELT development best practices and performance optimization;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Added Advantage</strong>: Certifications in Azure or GCP cloud platforms;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Domain Knowledge</strong>: Preferable to have knowledge of Oracle NetSuite, BambooHR, Salesforce data ingestion, and PMO data operations;<br>&nbsp;●&nbsp;<strong data-stringify-type="bold">Soft Skills</strong>: Strong problem-solving skills, effective communication, and ability to work both independently and in cross-functional teams while mentoring junior engineers.</p>