Databricks Data Engineer - India
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Cogniify
Summary
The role involves supporting, maintaining, and optimizing existing Databricks-based data applications and production pipelines. You will collaborate with engineering teams to ensure system reliability, performance, and scalability while managing workspace configurations and data quality.
Job Description
Role Overview
We are looking for an experienced Databricks Data Engineer to support, maintain, and enhance existing Databricks-based data applications and pipelines. The role focuses on ensuring reliability, performance, and scalability of production Databricks workloads rather than building net-new platforms from scratch. You will work closely with data, analytics, and engineering teams to keep critical data applications stable, optimized, and aligned with business needs.
Key Responsibilities
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Support and maintain existing Databricks applications, notebooks, jobs, and Delta Lake pipelines in production.
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Monitor, troubleshoot, and resolve issues related to job failures, performance degradation, data quality, and cluster utilization.
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Optimize existing Spark jobs, SQL queries, and Delta tables for cost, performance, and reliability.
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Manage and improve Databricks workspace configurations, including clusters, job scheduling, access controls, and Unity Catalog (where applicable).
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Implement and maintain data quality checks, logging, alerting, and basic observability for Databricks workloads.
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Collaborate with stakeholders to understand requirements for enhancements or bug fixes on existing applications.
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Perform incremental improvements, refactoring, and technical debt reduction on current Databricks solutions.
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Ensure adherence to best practices around security, governance, and cost management within the Databricks environment.
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Document existing pipelines, dependencies, and operational runbooks.
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Participate in on-call or support rotations as needed to maintain production stability
Required Qualifications
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6–9 years of overall experience in data engineering, with strong hands-on experience in Databricks.
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Solid proficiency in Apache Spark (PySpark and/or Scala) and SQL.
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Proven experience supporting and optimizing production Databricks workloads (jobs, notebooks, Delta Lake, workflows).
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Strong understanding of Delta Lake concepts (ACID transactions, time travel, optimization techniques such as Z-ordering, vacuum, optimize).
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Experience with Databricks Job clusters, Interactive clusters, and performance tuning (partitioning, caching, shuffle optimization, autoscaling).
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Familiarity with data modeling, ETL/ELT patterns, and production data pipeline support.
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Experience working with cloud platforms (preferably Azure, AWS, or GCP) in the context of Databricks.
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Ability to troubleshoot complex Spark and Databricks issues independently.
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Strong communication skills and ability to work effectively with EST-aligned team.
Preferred Qualifications
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Experience with Unity Catalog, Databricks SQL, or Lakehouse architecture.
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Knowledge of CI/CD practices for Databricks (e.g., Databricks Asset Bundles, Git integration, Terraform/ARM templates).
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Familiarity with orchestration tools (Airflow, Azure Data Factory, or Databricks Workflows).
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Exposure to data quality frameworks, monitoring tools, or cost optimization initiatives on Databricks.
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Experience supporting analytics or BI teams consuming Databricks data products.
Why Join UsWhy Join Us?
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Join a team of industry veterans from Google, Meta, and top-tier tech companies.
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Work on impactful, high-scale projects with leading global clients.
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Enjoy a flexible, remote-first culture focused on innovation and excellence.
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Competitive salary, equity options, and continuous learning opportunities.
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Shape the future of cloud and AI infrastructure at a rapidly growing company.
Perks And Benefits Of Working With Us
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Internet allowance
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Laptop
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PF
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Paid PTO
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Annual Bonus
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Gratuity
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Yearly Team building experiences
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Mentorship and sponsorship opportunities
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Manager resources and support
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Life & accidental insurance for additional protection.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.
Cogniify helps enterprises move from AI pilots to industrialized impact.
Most organizations don’t struggle with ideas or models—they struggle with scaling AI safely, economically, and operationally. AI works in demos, but stalls when it meets real data, real costs, real operations, and real regulation.
That’s the gap we solve.
We work with leaders across Retail & CPG, Banking & Fintech, Insurance, Manufacturing, Energy & Utilities, Healthcare & Life Sciences, Telecom, Tech & Media, and Supply Chain to design and build the control layers that make AI production-ready.
Our work spans:
- Data industrialization and trusted enterprise foundations
- Real-time sensing and predictive intelligence
- Agentic planning and autonomous operations
- AI lifecycle management, MLOps & FinOps
- Responsible AI, governance, and regulatory readiness
We don’t sell tools.
We don’t run pilots for the sake of pilots.
We help organizations:
- scale AI without cloud bill shock
- move from dashboards to decisions
- Turn insights into execution
- Pass audits before regulators ask
- and make AI accountable at the P&L level
Cogniify exists to close the value gap between experimentation and execution so AI becomes a durable capability, not a recurring initiative.
From pilots to production.
From insight to action.
From AI ambition to AI control.
Founded
2024
Company size
51-200 employees
Industry
Business Consulting and Services
Org type
Privately Held
Headquarters
San Jose, California
Cogniify helps enterprises move from AI pilots to industrialized impact.
Most organizations don’t struggle with ideas or models—they struggle with scaling AI safely, economically, and operationally. AI works in demos, but stalls when it meets real data, real costs, real operations, and real regulation.
That’s the gap we solve.
We work with leaders across Retail & CPG, Banking & Fintech, Insurance, Manufacturing, Energy & Utilities, Healthcare & Life Sciences, Telecom, Tech & Media, and Supply Chain to design and build the control layers that make AI production-ready.
Our work spans:
- Data industrialization and trusted enterprise foundations
- Real-time sensing and predictive intelligence
- Agentic planning and autonomous operations
- AI lifecycle management, MLOps & FinOps
- Responsible AI, governance, and regulatory readiness
We don’t sell tools.
We don’t run pilots for the sake of pilots.
We help organizations:
- scale AI without cloud bill shock
- move from dashboards to decisions
- Turn insights into execution
- Pass audits before regulators ask
- and make AI accountable at the P&L level
Cogniify exists to close the value gap between experimentation and execution so AI becomes a durable capability, not a recurring initiative.
From pilots to production.
From insight to action.
From AI ambition to AI control.
Founded
2024
Company size
51-200 employees
Industry
Business Consulting and Services
Org type
Privately Held
Headquarters
San Jose, California