Data Engineer - Contractor

Jobgether; India; Remote; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Remote work

Contract role with client diversity

Job summary

Jobgether is seeking a Senior Data Engineer on a contractor basis, based in India. You will design and build scalable data platforms using Databricks, Spark, SQL, Delta Lake, and Microsoft Fabric, influencing data quality, governance, and analytics reliability.

You will own end-to-end data engineering lifecycle, collaborate with architects and stakeholders, and contribute to reusable engineering standards and frameworks across client engagements.

Qualifications

• 5+ years of professional experience in Data Engineering, Analytics Engineering, or Data Platform Development.
• Strong hands-on expertise with Databricks, Apache Spark/PySpark, SQL, Microsoft Fabric, Delta Lake, and data warehousing.
• Proven experience designing and implementing data pipelines, ETL/ELT solutions, lakehouse architectures, and data integration frameworks.

Responsibilities

• Design, develop, and maintain scalable data solutions across enterprise data platforms.
• Build and optimize data ingestion, ETL/ELT, transformation, orchestration, and integration pipelines.

Skills

Databricks

Spark/PySpark

SQL

Data Pipelines

Data Governance

Education

Bachelor’s degree

Tools

Terraform

Power BI

Azure DevOps

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer - Contractor based in India.

Join a data-focused engineering environment where you will help modernize enterprise data platforms across diverse client and industry landscapes. In this role, you will design and build scalable data solutions using Databricks, Microsoft Fabric, Spark, SQL, and Delta Lake. You will have a strong influence on data quality, automation, governance, and the reliability of analytics platforms. The position covers the full data engineering lifecycle, from architecture and development through testing, deployment, optimization, and support. You will collaborate closely with architects, business stakeholders, analytics specialists, and platform engineers. This is an opportunity to contribute to strategic data modernization initiatives while establishing reusable engineering standards and frameworks.

Accountabilities

• Design, develop, and maintain scalable data solutions using Databricks, Microsoft Fabric, Apache Spark, PySpark, SQL, and Delta Lake.
• Build and optimize enterprise-grade data ingestion, ETL/ELT, transformation, orchestration, and integration pipelines.
• Develop automation frameworks for data validation, testing, monitoring, deployment, and operational support.
• Own data engineering activities across the full lifecycle, including requirements gathering, solution design, development, testing, deployment, and ongoing support.
• Build automated QA, reconciliation, and validation frameworks for analytical and reporting solutions.
• Ensure enterprise datasets meet requirements for data quality, completeness, consistency, accuracy, and business-rule compliance.
• Develop and maintain lakehouses, warehouses, semantic models, and data marts within Microsoft Fabric.
• Implement and validate security and governance controls, including Row-Level Security (RLS).
• Support CI/CD, DevOps, DataOps, and Infrastructure-as-Code initiatives and deployment automation.
• Optimize Spark workloads and data platforms for improved performance, scalability, and cost efficiency.
• Collaborate with business stakeholders, architects, analytics teams, and platform engineers to deliver reliable, secure enterprise-grade solutions.
• Establish coding standards, reusable frameworks, engineering best practices, and data governance processes.
• Contribute to technical discussions, mentor other engineers, and independently drive engineering initiatives where required.

Requirements

• 5+ years of professional experience in Data Engineering, Analytics Engineering, or Data Platform Development.
• Strong hands-on expertise with Databricks, Apache Spark/PySpark, SQL, Microsoft Fabric, Delta Lake, and data warehousing.
• Proven experience designing and implementing data pipelines, ETL/ELT solutions, lakehouse architectures, and data integration frameworks.
• Strong knowledge of Databricks Workflows, Jobs, automation, and orchestration.
• Experience developing automated testing, data validation, QA, and reconciliation frameworks.
• Hands-on experience implementing CI/CD pipelines using Azure DevOps, GitHub, or comparable tools.
• Solid understanding of data quality, reconciliation, metadata management, data governance, and security practices.
• Experience with performance tuning and optimization of Spark-based workloads.
• Practical experience with Microsoft Fabric components, including Data Factory, Lakehouse, Warehouse, Semantic Models, and Power BI.
• Experience with Infrastructure-as-Code tools such as Terraform, Bicep, or ARM Templates is preferred.
• Familiarity with DataOps and MLOps practices is an advantage.
• Knowledge of Power BI semantic models, DAX, and analytical reporting solutions is beneficial.
• Experience working with enterprise data governance and security frameworks is preferred.
• Exposure to Azure, AWS, or GCP cloud environments is an advantage.
• Strong analytical and problem-solving abilities, with excellent communication and stakeholder-management skills.
• Ability to work independently, lead initiatives, collaborate effectively across functions, and connect technical solutions to broader business objectives.
• A Bachelor’s degree or equivalent educational qualification.

Benefits

• Full-time contractor opportunity within a data and technology-focused environment.
• Opportunity to work on strategic data modernization initiatives across multiple clients and industry domains.
• Exposure to modern data technologies, including Databricks, Microsoft Fabric, Spark, Delta Lake, Azure, and Power BI.
• Opportunity to work on enterprise-scale data platforms, automation, data quality, analytics, and governance initiatives.
• Collaborative environment with experienced data engineering, analytics, architecture, and technology professionals.
• Scope to take ownership of technical initiatives and contribute to engineering standards and reusable frameworks.
• Opportunities to expand expertise across cloud data platforms, DataOps, DevOps, automation, and data governance.
• Location: India, with the role associated with Hyderabad, Mumbai, and Bangalore.
• Work arrangement: Remote.