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 general 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 "RiseTM."
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 Senior Data Engineer: The Challenge (Responsibilities) Work with cutting-edge big data platforms (e.g., Databricks, Apache Spark) at a large scale, pushing the boundaries of data processing and model enablement.
Build and maintain robust ETL/ELT pipelines for the ingestion, transformation,



and aggregation of large-scale datasets on Hadoop and enterprise data platforms.
Develop high-performance data processing jobs using PySpark/Spark and Python on data platforms such as Cloudera and Databricks.
Optimize pipeline performance and cost through partitioning, file formats, compute tuning, and efficient query patterns.
Contribute to CI/CD for data workflows (testing, code reviews, deployment automation), promoting engineering best practices and maintainable codebases.
Partner with Product Managers to develop a deep understanding of users and use cases and apply that knowledge to scoping and building new modules and features.
Your Profile (Requirements) Strong hands-on experience in data engineering, building production-grade pipelines on big data platforms (Hadoop ecosystem and cloud data platforms, specifically Databricks).
High proficiency in using Python, Spark, Hadoop platforms tools (Hive, Impala, Airflow, NiFi), and SQL to build Big Data products.
Hands-on experience with cloud data platforms such as Databricks and Snowflake (Databricks preferred).
Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, or Talend.
Working knowledge of DevOps/CI-CD practices: version control (Git), automated testing, release pipelines, and observability.
Strong problem-solving skills with the ability to debug complex data issues and communicate clearly with technical and non-technical stakeholders.




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 developing Java-based applications is an added advantage.
Familiarity with cloud-native foundations or AI coding assistants.
Languages Advanced Oral English: For seamless collaboration with global teams.
Advanced Spanish.
Special Notes Our Client is seeking proactive engineers ready to push the boundaries of large-scale data processing.
Work Arrangement We value flexibility to support your lifestyle.
This position is available as: Remote 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 : / Keywords: Databricks, Apache Spark, Hadoop, Python, ETL/ELT Strong hands-on experience in data engineering building production-grade pipelines on big data platforms (Hadoop ecosystem and cloud data platforms - databricks).
High proficiency in using Python, Spark, Hadoop platforms tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products.
Hands-on experience with cloud data platforms such as databricks, snowflake (databricks preferred) Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, or Talend.
Working knowledge of DevOps/CI-CD practices: version control (Git), automated testing, release pipelines, and observability.
Strong problem-solving skills with the ability to debug complex data issues and communicate clearly with technical and non-technical stakeholders.
Experience developing Java based applications is an added advantage.

📌 Data Engineer Sr (Xico)
🏢 Sequoia Connect
📍 Xico