Data Engineer

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      "Value": "<ol><li style=\"list-style-type:none\"><span style=\"font-size:18pt\"><span style=\"tab-stops:.4in\"><span new=\"\" roman=\"\" style=\"font-family:\" times=\"\"><a name=\"_Toc120876405\"> </a></span></span></span></li></ol><p><strong>Data Engineer Snowflake</strong></p><p>&nbsp;</p><p>Join an amazing company where you can work with cutting-edge technologies and platforms. Give your career an Infinite edge, with a stimulating environment and a global work culture. Be a part of an organization where we celebrate integrity, innovation, collaboration, teamwork, and passion. A culture where every employee is a leader delivering ideas that make a difference to this world we live in.</p><p>&nbsp;</p><p><strong>In the Database Analysis - Sr Professional II role&nbsp; responsibilities include, although not limited to:</strong></p><ul><li>Architect and build enterprise-grade data solutions leveraging Snowflake as the core data platform.</li><li>Lead the implementation of scalable data models, robust data pipelines, and governed Lakehouse architectures supporting analytics and machine learning.</li><li>Design and optimize Snowflake schemas using best practices in secure data sharing, micro-partitioning, storage strategies, and compute tuning.</li><li>Build and manage real-time ingestion and event-driven architectures using Kafka integrated with Snowflake.</li><li>Implement and enforce enterprise data governance, privacy, data quality, lineage, and strong access controls (RBAC) in Snowflake environments.</li><li>Establish standards for Snowflake performance tuning, cost optimization, workload management, and query efficiency using platform metrics.</li><li>Integrate Snowflake with APIs, cloud services, microservices, and ingestion/orchestration tools such as Databricks, ADF, Spark, or Kafka Connect.</li><li>Solve complex issues related to ingestion failures, pipeline orchestration, schema evolution, and transformation logic across platforms.</li><li>Mentor developers and data engineers on Snowflake usage patterns, modeling strategies, and best practices for building reusable data products.</li></ul><p>&nbsp;</p><p><strong>In addition to the qualifications listed below, the ideal candidate will demonstrate the following traits:</strong></p><ul><li>Strong analytical mindset with ability to optimize systems at scale.</li><li>Passion for platform maturity, best practices, and mentoring others.</li><li>Ability to troubleshoot complex data challenges across distributed systems.</li><li>Clear communication when collaborating with engineering, architecture, and business teams.</li><li>Ownership-driven and proactive approach to cost efficiency, data quality, and platform security.</li></ul><p>&nbsp;</p><p><strong>You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.</strong></p><p>&nbsp;</p><p><strong>Minimum Qualifications:</strong></p><ul><li>Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, or related field.</li><li>7+ years in data engineering, including hands-on experience designing and optimizing Snowflake environments.</li><li>Expert-level SQL&nbsp;skills, with strong knowledge of micro-partitions, warehouses, clustering, caching, and query tuning in Snowflake.</li><li>Proven experience building ETL/ELT pipelines&nbsp;specifically optimized for Snowflake workloads.</li><li>Experience using Kafka&nbsp;for real-time or event-driven ingestion into Snowflake or dependent systems.</li><li>Proficiency in Python, Scala, C#, or Java for transformations, orchestration logic, and automation.</li><li>Solid knowledge of data warehousing, dimensional modeling, and/or Lakehouse architectures.</li><li>Strong Snowflake security expertise (RBAC, encryption, masking, access policies) and governance frameworks.</li><li>Ability to independently lead design decisions and drive Snowflake platform adoption.</li><li>Strong English verbal and written communication skills, including executive presentation capabilities.</li></ul><p>&nbsp;</p><p><strong>Preferred Qualifications:</strong></p><ul><li>Experience with advanced Snowflake capabilities: Snowpipe, Streams, Tasks, Replication, Time Travel, Search Optimization Service.</li><li>Background with complementary tools such as Spark, Kafka Connect, Databricks, Azure Data Factory, Airflow, or Prefect.</li><li>Experience with Snowflake cost governance, workload isolation, marketplace integration, or cross-cloud data sharing.</li><li>Familiarity with Agile/Scrum methodologies and ability to collaborate in cross-functional engineering teams.</li></ul>",
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