Sr Data Engineer

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 global IT powerhouse that represents the connected world through innovative, customer-centric experiences. As a USD 6 billion organization and one of the top 7 IT service providers globally, our client empowers over 1,200 global customers—including several Fortune 500 companies—to "Rise™." With a massive network of 163,000+ professionals across 90 countries, they are at the absolute forefront of digital transformation, leveraging next-generation technologies such as 5G, AI, Blockchain, and Quantum Computing. This is your chance to thrive in a workplace recognized as one of the most sustainable corporations in the world. You will join an environment that values innovation and societal impact, working on end-to-end digital transformation projects for global leaders. If you are a driven professional looking for global career opportunities and exposure to high-impact projects within an international network of expertise, this is where you belong. We are currently searching for a Sr Data Engineer: Client Overview Our Client is seeking a Sr Data Engineer to join their team. This role ensures that data is accessible, reliable, secure, and optimized for performance across enterprise platforms. The Challenge (Responsibilities) - Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time data processing. - Build and optimize data models, Delta Tables, and Lakehouse architectures to support analytics and reporting. - Develop and integrate RESTful APIs and data services to facilitate seamless data exchange across enterprise systems. - Implement real-time and high-frequency data ingestion frameworks using streaming technologies and event-driven architectures. - Design and manage cloud-native data solutions leveraging Azure services including Azure Data Factory, Azure Databricks, ADLS, Event Hubs, and Synapse Analytics. - Develop and optimize Databricks Spark applications for large-scale data transformation and processing. - Ensure data quality, governance, security, and compliance across data platforms. - Collaborate with data scientists, analysts, application teams, and business stakeholders to deliver scalable data solutions. - Troubleshoot, monitor, and optimize pipeline performance and data platform reliability. - Support DataOps and CI/CD practices for data pipeline deployment and automation. Your Profile (Requirements) - Strong proficiency in SQL and relational databases such as Oracle, SQL Server, and MySQL. - Strong programming skills in Python, PySpark, PL/SQL, Java, or Scala. - Hands-on experience with Azure Cloud technologies (ADF, Azure Databricks, ADLS, Azure Synapse Analytics, Azure Event Hubs, Azure Functions, Azure API Management, Azure DevOps). - Experience with Databricks Lakehouse architecture, Delta Lake, and Delta Tables. - Expertise in API development, API integration, RESTful services, and microservices architecture. - Experience processing high-volume and high-frequency data with low-latency requirements. - Strong knowledge of real-time data ingestion and streaming technologies such as Kafka, Azure Event Hubs, or Kinesis. - Experience with Spark, Hadoop, and distributed data processing frameworks. - Hands-on experience with OpenShift, Kubernetes, Docker, and containerized deployments. - Experience with workflow orchestration tools such as Apache Airflow and Azure Data Factory. - Understanding of data governance, data security, and compliance best practices. - 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 Delta Live Tables (DLT), Auto Loader, and Change Data Capture (CDC). - Knowledge of DataOps, CI/CD, and Infrastructure as Code (IaC). - Familiarity with event-driven architectures and real-time analytics platforms. - Azure Data Engineer (DP-203) and Databricks certifications. - Familiarity with cloud-native foundations or AI coding assistants. Languages - Advanced Oral English: For seamless collaboration with global teams. - Advanced Spanish. Work Arrangement We value flexibility to support your lifestyle. This position is available as: - Remote (Depending on specific project needs). 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 - Strong proficiency in SQL and relational databases (Oracle, SQL Server, MySQL). - Strong programming skills in Python, PySpark, PL/SQL, Java, or Scala. - Hands-on experience with Azure Cloud technologies (ADF, Databricks, ADLS, Synapse, Event Hubs). - Experience with Databricks Lakehouse architecture, Delta Lake, and Delta Tables. - Expertise in API development, RESTful services, and microservices architecture. - Experience with real-time data ingestion and streaming (Kafka, Event Hubs, Kinesis). - Experience with Spark, Hadoop, and distributed frameworks. - Hands-on experience with OpenShift, Kubernetes, Docker. - Experience with workflow orchestration tools (Apache Airflow, ADF). Originally posted on Himalayas