Data Engineer ID89384

AgileEngine, LLC.; Pune District; Remote; INR 1,200,000 - 1,600,000; Full time

Benefits offered by this job

Remote work

Local presence in India

Competitive INR compensation

Exciting projects

Job summary

AgileEngine, LLC. is seeking a Data Engineer in India (Pune region) with strong Databricks, PySpark and GCP experience to design and productionize scalable ETL/ELT pipelines and agentic workflows for data engineering automation.

You will work on modern lakehouse architectures, Delta Lake integration, and data quality across global client projects, with remote-friendly setup and local Indian compliance.

Qualifications

• 5+ years of hands-on Databricks and PySpark experience
• Advanced SQL and data-processing skills
• Hands-on GCP experience (BigQuery)
• Experience with Delta Lake and modern lakehouse architectures
• Strong ETL/ELT, data pipeline design, performance optimization and data quality
• Production-grade data solutions delivery
• Upper-intermediate English level

Responsibilities

• 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
• Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake environments
• Develop data pipelines and reusable frameworks to support various use cases
• Implement data quality checks, monitoring, validation, and production controls
• Optimize PySpark and SQL workloads for performance and scalability
• Support testing, deployment, productionization, troubleshooting and enhancement of data solutions
• Collaborate with business, data engineering and platform teams to identify automation opportunities

Skills

Databricks

PySpark

Advanced SQL

BigQuery

Delta Lake

ETL/ELT

Data pipelines

Production-grade

English proficiency

Job description

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.

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.