Senior Databricks Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Databricks Engineer in India.

This role offers an exciting opportunity to design and build scalable Data & AI platforms that power enterprise-wide analytics, machine learning, and strategic decision-making initiatives.

You will play a key role in developing modern cloud-native data architectures using Databricks and Medallion Architecture principles to manage large-scale data workflows and ELT pipelines.

The position combines advanced data engineering, platform integration, governance, and AI-ready infrastructure development within a highly collaborative and innovation-driven environment.

You will work closely with data, analytics, and AI teams to ensure reliable, secure, and high-quality data delivery across multiple enterprise systems and business functions.

The role also provides strong exposure to cloud technologies, automation frameworks, MLOps processes, and enterprise-grade data governance practices.

Ideal for professionals passionate about scalable data ecosystems and modern data engineering, this opportunity offers the chance to contribute directly to impactful enterprise transformation initiatives.

Accountabilities

• Design, build, and optimize scalable ELT pipelines and workflows using Databricks, Apache Spark, and Delta Lake technologies.
• Implement and maintain Medallion Architecture data layers, including bronze, silver, and gold data processing pipelines.
• Develop automated orchestration workflows, dependency management systems, and monitoring processes for enterprise-scale data operations.
• Integrate enterprise platforms such as PeopleSoft, D2L, and Salesforce into centralized data ecosystems using APIs and integration frameworks.
• Build ingestion frameworks capable of handling structured, semi-structured, and unstructured data sources efficiently.
• Implement data quality checks, validation rules, monitoring systems, and anomaly detection mechanisms to ensure data reliability and integrity.
• Support centralized metadata management, lineage tracking, and governance policy enforcement using Unity Catalog or similar tools.
• Design and enforce data security, privacy, encryption, masking, and access control practices aligned with compliance requirements such as GDPR and FERPA.
• Collaborate with AI/ML teams to deliver feature-rich datasets, reusable feature stores, and scalable MLOps workflows using MLflow.

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• Architect and optimize cloud-based data lakes and storage solutions across platforms such as ADLS or Amazon S3.
• Maintain technical documentation, architecture diagrams, data dictionaries, and operational runbooks.
• Participate in code reviews, stakeholder enablement, and continuous improvement initiatives across the data engineering ecosystem.
  
  

Requirements

• Strong hands-on experience with Databricks, Delta Lake, and Apache Spark for enterprise-scale data engineering.
• Deep understanding of ELT pipeline development, orchestration, monitoring, and cloud-native data platform design.
• Proven experience implementing Medallion Architecture and managing enterprise-grade data versioning and schema enforcement.
• Strong programming skills in SQL, Python, or Scala for workflow development and data transformation logic.
• Experience integrating enterprise applications such as PeopleSoft, Salesforce, or D2L into centralized data platforms.
• Familiarity with data governance, metadata management, lineage tracking, and observability tools.
• Experience with Unity Catalog, MLflow, or similar governance and MLOps frameworks is preferred.
• Knowledge of cloud platforms such as Microsoft Azure or Amazon Web Services, including storage, networking, and security concepts.
• Understanding of data warehouse design principles and dimensional modeling techniques such as star and snowflake schemas.
• Strong analytical, problem-solving, and communication skills with the ability to collaborate across technical and business teams.
  
  

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Benefits

• Fully remote work flexibility within India.
• Opportunity to work on advanced enterprise Data & AI transformation initiatives.
• Exposure to modern cloud-native architectures, MLOps workflows, and scalable analytics ecosystems.
• Collaborative and innovation-driven work environment with cross-functional teamwork opportunities.
• Career growth opportunities through hands-on experience with enterprise-scale data engineering technologies.
• Opportunity to contribute to strategic AI, machine learning, and analytics initiatives.
• Dynamic and technology-focused culture emphasizing continuous learning and professional development.
  
  

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. 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.