Job Description
Team: IT
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.
- 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.
- 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.
- 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.
Requirements:
Benefits:
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Date Posted
05/15/2026
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