高级数据工程师

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