Data Engineer Sr

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 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.

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High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.

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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

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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 :
Requirements

- 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.

Originally posted on Himalayas