Sr Data Engineer
Sequoia Connect Ciudad de México, Mexico
IT Services and IT Consulting · 11-50 employees
About the role
Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time data processing using cloud-native technologies. Collaborate with cross-functional teams to ensure data quality, security, and performance optimization across enterprise platforms.
What they look for
Requirements
Requires strong proficiency in SQL, Python, and Azure cloud technologies including Databricks and Synapse Analytics. Candidates must have experience with distributed data processing frameworks, API development, and real-time streaming architectures.
Full 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: https://www.sequoia-connect.com/careers/
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).
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