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Data Engineer

Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL, and operationalize agentic workflows for data engineering automation.

  • Remote, India
  • Remote
  • Posted Nov 10, 2026
INDUSTRYSoftware & InternetData & Analytics

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 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.

Requirements

Nice to have: AI/agentic workflows, AI agents, workflow automation, orchestration frameworks, reusable data engineering frameworks, platform components

Skills

DatabricksPySparkSQLGCPBigQueryDelta LakeETL/ELTdata pipeline designperformance optimizationdata qualitysoftware engineering practicesversion controldeploymentmonitoringproduction supportDatabricksPySparkSQLGCPBigQueryDelta Lake

Full 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 hands-on experience with Databricks and PySpark, advanced SQL, GCP, Delta Lake, modern lakehouse architectures, and an upper-intermediate English level. 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. 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. 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.

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