Eassy Onboard
https://eassyonboard.comAbout
We are a team of Databricks Certified Data Engineers dedicated to empowering businesses in the data-driven world. Our expertise spans designing automated workflows, scalable architectures, optimized data pipelines, performance-tuned Databricks environments, and Agentic AI solutions. We help organizations reduce manual effort, optimize costs, and unlock faster, more reliable insights. Across every engagement, we ensure secure data transfers, strong data integrity, and robust validation processes—so companies can fully trust their data operations.
In addition to delivering enterprise-grade data and AI solutions, we operate as an Employer of Record (EOR), enabling foreign companies to seamlessly hire top Indian talent without the complexity of local payroll, compliance, or statutory requirements. We manage employment, payroll, taxation, and regulatory compliance end-to-end, while ensuring hired professionals work exclusively for our client organizations.
With a dual focus on enterprise transformation and global talent enablement, we help companies scale their data capabilities faster while building reliable, compliant, and future-ready teams in India.
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Company Description
Eassy Onboard LLP is a team of Databricks Certified Data Engineers committed to empowering businesses through data-driven solutions. Specializing in automated workflows, scalable architectures, optimized data pipelines, and AI solutions, we help organizations reduce manual effort, optimize costs, and achieve reliable insights. We ensure secure data operations with robust validation processes and strong data integrity. As an Employer of Record (EOR), we assist global companies in hiring top Indian talent, managing payroll, compliance, and regulatory requirements. Our mission is to accelerate enterprise transformation and enable companies to build future-ready, compliant teams.
Role Description
We are seeking a Senior Data Engineer with deep expertise in Spark/PySpark/SQL to join our data team.
This is a hands-on technical role for someone passionate about building scalable data systems, mentoring engineers, and shaping data strategy.
You will architect systems that power high-performance data processing, enable advanced analytics, and accelerate AI initiatives.
What You'll Do
- Design and evolve scalable, distributed data infrastructure across cloud platforms including GCP and AWS.
- Build and maintain real-time and batch data processing pipelines supporting AI/ML workloads, consumer applications, and analytics.
- Develop and manage integrations with third-party e-commerce platforms to expand the data ecosystem.
- Ensure data availability, reliability, and quality through monitoring and automated auditing.
- Partner with engineering, AI, and product teams on data solutions for business-critical needs.
- Mentor and support data engineers, establishing best practices and code quality standards.
Qualifications
- Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
- 5+ years of software development and data engineering experience with ownership of production-grade data infrastructure.
- Deep expertise scaling Spark, PySpark, and SQL in production, including Databricks or DataProc on GCP.
- Strong understanding of distributed computing and modern data modeling for scalable systems.
- Proficient in Python with experience implementing software engineering best practices.
- Hands-on experience with both relational and NoSQL systems including MySQL, MongoDB, and Elasticsearch.
- Strong communicator with experience influencing cross-functional stakeholders.
Nice to Have
- Experience with job orchestration and containerization tools such as Airflow and Docker.
- Experience working with vector stores and knowledge graphs.
- Experience working in early-stage, high-growth environments.
- Familiarity with MLOps pipelines and integrating ML models into data workflows.
- A proactive, problem-solving mindset with a passion for innovative solutions.
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