Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in India. This role is an opportunity to contribute to the design and delivery of scalable, cloud-based data solutions within a modern data engineering environment. You will work on building and optimizing ETL/ELT pipelines that enable reliable data flow across multiple systems and business domains. The position involves hands-on development using Python, PySpark, and SQL, with a strong focus on Azure cloud technologies. You will collaborate closely with data analysts, engineers, and business stakeholders to transform raw data into meaningful, high-quality insights. This is a highly collaborative and technically engaging role where your work directly supports data-driven decision-making. You will also be involved in improving data reliability, performance, and governance across evolving data platforms. Accountabilities

• Design, develop, and maintain scalable ETL/ELT pipelines to support efficient data integration and processing across multiple sources.
• Build and optimize data processing workflows using Python and PySpark for batch and large-scale data workloads.
• Ingest and transform data from APIs, databases, files, and streaming systems into structured formats for analytics and reporting.
• Write and optimize SQL queries to support data transformation, reporting, and performance-efficient data retrieval.
• Monitor, troubleshoot, and improve existing data pipelines to ensure reliability, scalability, and performance.
• Support data quality, validation, and governance initiatives, including metadata management and data lineage tracking.
• Work with Azure Data Factory, Azure Data Lake, and Azure Databricks to develop and maintain cloud-native data solutions.
• Collaborate in Agile environments, participating in sprint planning, code reviews, and cross-functional delivery cycles.

Requirements

• 2-4 years of experience in data engineering or related roles, with hands-on exposure to building data pipelines and cloud-based solutions.
• Strong proficiency in Python, SQL, and PySpark for data processing and transformation.
• Experience working with Microsoft Azure services such as Azure Data Factory, Azure Data Lake, and Azure Databricks.
• Solid understanding of ETL/ELT architecture, data integration patterns, and data warehousing concepts.
• Familiarity with version control tools such as Git and basic understanding of CI/CD practices.
• Exposure to streaming technologies such as Apache Kafka is an added advantage.
• Strong analytical thinking, problem-solving skills, and ability to work both independently and in Agile team environments.
• Good communication skills with the ability to collaborate effectively with technical and non-technical stakeholders.

Benefits

• Remote-friendly work environment with flexible engagement options
• Opportunity to work with modern cloud data technologies (Azure ecosystem)
• Career growth in a fast-evolving data engineering and analytics environment
• Exposure to large-scale data pipelines and enterprise-level data systems
• Collaborative, Agile-driven engineering culture
• Learning opportunities in data engineering, cloud architecture, and data governance practices
• Inclusive work environment focused on continuous improvement and technical excellence

How Jobgether Works We use an

AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.