Accountabilities

Design, develop, and maintain scalable data processing systems capable of handling large volumes of structured and unstructured data.

Build and manage data pipelines for data ingestion, processing, transformation, integration, and storage.

Optimize data infrastructure, workflows, and processing systems to improve performance, scalability, and reliability.

Collaborate with data scientists, data analysts, and other technical stakeholders to understand data requirements and deliver appropriate engineering solutions.

Troubleshoot and resolve data pipeline, integration, quality, and infrastructure issues in a timely manner.

Monitor system performance and data quality, implementing improvements to maintain operational stability.

Apply engineering best practices across data ETL, streaming, warehousing, orchestration, and quality assurance.

Stay up to date with emerging technologies, tools, and trends in big data and cloud engineering.

Mentor junior data engineers, sharing technical knowledge and promoting best practices across the team.

Requirements:

Bachelor's or master's degree in Computer Science, Data Science, Statistics, or a related field.

Strong professional experience in data engineering, including the design and implementation of scalable data solutions.

Proficiency in Python and experience with Apache Spark and Apache Kafka.

Experience with cloud platforms and the Databricks ecosystem.

Knowledge of data ETL, data integration, streaming, data quality, and data warehousing concepts.

Experience with Snowflake and performance optimization of data systems.

Familiarity with Docker, Kubernetes, Git, and process orchestration tools.

Understanding of quality assurance practices and system performance monitoring.

Ability to collaborate effectively with data scientists, analysts, and cross-functional technical teams.

Strong troubleshooting and analytical skills, with a proactive approach to resolving complex technical challenges.

Good communication skills and the ability to mentor and support less experienced engineers.

Proficiency in English at C2 level.

Relevant Certifications:

Microsoft Certified: Azure Solutions Architect Expert.

Databricks Certified Associate Developer for Apache Spark 3.0.

Databricks Certified Data Engineer Professional.

Microsoft Certified: Azure Data Engineer Associate.

Benefits:

Fully remote work arrangement within India.

Full-time, regular employment.

Opportunity to contribute to AI-powered transformation and technology initiatives for global enterprises.

Hands-on experience with advanced data engineering and cloud technologies.

Mentorship and access to professional development opportunities.

Learning resources and opportunities to strengthen technical expertise.

Collaborative environment focused on innovation, continuous learning, and career growth.

Inclusive, values-driven workplace that promotes respect, integrity, and equal opportunity.

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.

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