Data Engineer ID89384

We are looking for a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

The mandatory requirements are 5+ years of experience with Databricks and PySpark, advanced SQL, hands-on GCP experience, and experience with Delta Lake and modern lakehouse architectures.

RECRUITMENT PROCESS

1. Application — Share a few details about your experience and background.

2. Coding Challenge — If applicable, complete it in the coding language you are most comfortable with.

3. Video Interview — Record a short video introduction in English.

4. Technical Interview or Hiring Manager Interview — Discuss your experience and fit for the role.

5. Offer — If it’s a match, you’ll receive an offer.

WHAT YOU’LL GAIN

• Remote work — Work from where you feel most productive.

• Local presence in India — Work in a structured and compliant environment aligned with Indian regulations.

• Competitive compensation in INR — Receive compensation in INR, plus support for learning, education, and wellness.

• Exciting projects — Work with modern technologies for global clients and fast-growing companies.

MUST HAVES

• 5+ years of strong hands-on experience with Databricks and PySpark.

• Advanced SQL and data-processing skills.

• Hands-on experience with GCP, particularly BigQuery.

• Experience with Delta Lake and modern data lake/lakehouse architectures.

• Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.

• Experience building reliable, scalable, production-grade data solutions.

• Strong analytical and troubleshooting skills.

• Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.

• Upper-intermediate English level.

NICE TO HAVES

• Experience developing or integrating AI/agentic workflows, AI agents, or workflow automation solutions.

• Experience applying AI to automate data engineering, validation, troubleshooting, or operational processes.

• Familiarity with orchestration and automation frameworks.

• Experience developing reusable data engineering frameworks and platform components.

• Exposure to productionizing AI-enabled solutions with appropriate validation, monitoring, and human oversight.

WHAT YOU WILL DO

• Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.

• Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.

• Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.

• Develop data pipelines and reusable frameworks and components to support new business requirements and datasets across multiple use cases.

• Implement data quality checks, monitoring, validation, exception handling, and production controls.

• Optimize PySpark and SQL workloads for performance, reliability, and scalability.

• Support testing, deployment, productionization, troubleshooting, and ongoing enhancement of data and agentic solutions.

• Collaborate with business, data engineering, and platform teams to identify further automation opportunities.