Sr Data Engineer

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 1200 global customersincluding several Fortune 500 companiesto Rise. With a massive network of 163000 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 Careers Page:
Azure Databricks PySpark Azure Data Factory ETL/ELT Kafka

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).