Senior Data Engineer at Eassy Onboard · Remote only · 4 - 8 years · ₹25L - ₹50L / yr · Raised funding · Remote only · Posted 17 May 2026

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.

About Eassy Onboard
About
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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We are looking for experienced Senior Data Engineers with strong hands-on expertise in Google Cloud Platform (GCP), Python, PySpark, and SQL. Candidates with team lead experience will be preferred.
📌 Job Details:
- Role: Senior GCP Data Engineer
- Experience: 8+ Years
- Budget: Up to ₹30 LPA
- Location: Bangalore / Hyderabad
- Relocation: Candidates from Chennai and Pune willing to relocate are welcome.
- Notice Period: Immediate to 15 days
- Interview Process: L1 – Virtual | L2 / DM – Face-to-Face (F2F)
💻 Required Technical Skills:
- Strong hands-on experience with GCP data engineering.
- Excellent proficiency in Python, PySpark, and SQL.
- Experience in designing, developing, and optimizing data pipelines.
- Good understanding of ETL/ELT processes and large-scale data processing.
- Experience working with cloud-based data platforms and data warehousing.
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- Previous experience as a Technical Lead or leading a data engineering team.
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Job Description: Python + AI
Company: Wissen Technology
Location: Bangalore, India
Experience: 5+Years
Employment Type: Full-Time
Role: Python + AI / Data Engineer
About the Role
Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.
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- Design, develop, and maintain scalable data pipelines using Python and PySpark.
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- Build and optimize data processing solutions using Apache Spark / PySpark.
- Develop data ingestion and transformation pipelines into Snowflake.
- Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
- Work with batch and, where applicable, real-time data processing pipelines.
- Build and integrate AI and Generative AI solutions using Python.
- Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
- Integrate AI models with enterprise data platforms and data pipelines.
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- Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
- Implement data pipeline monitoring, logging, error handling, and alerting.
- Work with cloud platforms such as AWS, Azure, or GCP.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
- Participate in technical design, architecture, code reviews, and production support.
- Mentor junior engineers and contribute to engineering best practices.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience working on enterprise-scale AI and data engineering projects.
- Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
- Experience with Databricks is an advantage.
- Experience with AI Agents / Agentic AI and tool/function calling.
- Knowledge of distributed systems and cloud-native architecture.
- Experience leading technical initiatives or mentoring engineering teams.
Job Title : Senior Data Engineer – Databricks
Experience : 14 to 20 Years
Location : HSR Layout, Bangalore
Work Mode : Hybrid – 3 Days WFO
Shift : 11:30 AM – 07:30 PM IST
Positions : 2
Notice Period : Immediate Joiners Only
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We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.
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Must-Have Skills :
- 14 to 20 years of Data Engineering experience
- Databricks & Apache Spark / PySpark
- Python & SQL
- AWS Cloud
- Lakehouse Architecture
- ETL / ELT & Distributed Data Processing
- Batch & Streaming Pipelines
- Data Pipeline Optimization & Data Modeling
- CDC & Incremental Processing
- Git, CI/CD & Testing
- Data Quality, Monitoring & Observability
- Technical Leadership & Stakeholder Management
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- Design scalable data architectures and data models.
- Implement data quality, monitoring, lineage, and CI/CD practices.
- Lead technical discussions and mentor engineering teams.
- Collaborate with business stakeholders, architects, product owners, and engineering teams.
- Remain hands-on while providing technical leadership.
Ideal Candidate :
A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.
🔴 Super Urgent : Only Bangalore-based immediate joiners.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
About the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
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- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
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Job Title : Senior Data Engineer – GCP & Apache Spark
Job Details :
- Number of Positions : 3
- Employment Type : Contract-to-Hire (C2H)
- Experience Required : 5 to 8 Years
- Location : Manyata Tech Park, Bengaluru
- Work Mode : Hybrid – 3 Days in Office per Week
- Preferred Notice Period : Immediate to 15–20 Days
- Project Duration : Initially 6–8 months, with a strong possibility of extension for long-term projects
- Relocation : Candidates from outside Bengaluru can apply if they are willing to relocate.
Role Overview :
We are looking for experienced Senior Data Engineers with strong expertise in Google Cloud Platform (GCP), Apache Spark, BigQuery, and SQL to design, develop, and maintain scalable data pipelines and distributed data processing solutions.
The ideal candidate should have hands-on experience with cloud-based data engineering, end-to-end pipeline architecture, system design, performance optimization, debugging, and CI/CD practices.
Mandatory skills :
Apache Spark (PySpark / Scala), SQL, GCP, BigQuery, GCP Dataproc, Data Pipelines, System Design, CI/CD, Debugging & Problem-Solving.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines using Apache Spark, PySpark, and/or Scala.
- Build and optimize batch and distributed data processing workflows on GCP.
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- Develop and maintain data workflows using GCP services, including Dataproc, BigQuery, and Cloud Storage.
- Design end-to-end data pipeline architectures with a focus on scalability, reliability, and performance.
- Write and optimize complex SQL queries for large-scale datasets.
- Troubleshoot and resolve data processing issues, pipeline failures, and performance bottlenecks.
- Implement CI/CD practices for data engineering workflows, testing, and deployments.
- Monitor pipeline performance and identify opportunities for continuous improvement.
- Collaborate with cross-functional teams to understand requirements and deliver reliable data solutions.
- Participate in code reviews, testing, production deployments, and production support.
Mandatory Skills :
- Strong hands-on experience with Apache Spark, including PySpark and/or Scala.
- Strong SQL skills and experience working with large-scale datasets.
- Hands-on experience with Google Cloud Platform (GCP).
- Practical experience with BigQuery and data warehousing concepts.
- Working knowledge of GCP Dataproc.
- Strong understanding of data pipelines, end-to-end workflows, and system design.
- Practical experience with CI/CD and deployment processes.
- Excellent debugging, troubleshooting, and problem-solving skills.
Preferred Skills :
- Experience with Apache Airflow, Google Cloud Composer, or similar orchestration tools.
- Knowledge of Kafka or other streaming and messaging technologies.
- Proficiency in Python for data engineering and automation.
- Experience with Git-based development workflows.
- Knowledge of Linux/Unix environments and shell scripting.
- Familiarity with monitoring, logging, data quality, and governance practices.
Required Qualifications :
- 5 to 8 years of experience in Data Engineering, Big Data Engineering, or a related field.
- Proven experience developing and maintaining scalable data pipelines.
- Strong understanding of distributed data processing and cloud-based data architecture.
- Ability to troubleshoot complex technical issues and optimize pipeline performance.
- Strong communication, collaboration, and ownership skills.
Interview Process :
Round 1 : AI-Based Interview
- Candidates must complete the AI interview as soon as possible after receiving the invitation.
Round 2 : Virtual Interview Drive
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