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Sequoia Connect

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Sr Data Engineer

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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).

Skills

What Senior Data Engineering jobs ask for — and how much of it you have →

See also

Data Engineering jobs by country — openings, pay and top skills →

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