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Salary
≈ $33k – $83k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Senior · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Aug 18, 2026.

Overview
Company
Impact
Profile match
Cognida helps enterprises and AI builders turn frontier AI into dependable production systems across data, applications, workflows, integrations, and governance.

About Cognida.ai

Our Purpose is to boost your competitive advantage using AI and Analytics.

We Deliver tangible business impact with data-driven insights powered by AI. Drive revenue growth, increase profitability and improve operational efficiencies.

We Are technologists with keen business acumen - Forever curious, always on the front lines of technological advancements. Applying our latest learnings, and tools to solve your everyday business challenges.

We Believe the power of AI should not be the exclusive preserve of the few. Every business, regardless of its size or sector deserves the opportunity to harness the power of AI to make better decisions and drive business value.

We See a world where our AI and Analytics solutions democratise decision intelligence for all businesses. With Cognida.ai, our motto is ‘No enterprise left behind’.

A highcaliber Data & AI Engineer who can operate independently while seamlessly collaborating across global time zones.

Position Overview

We are seeking a dynamic, self-driven Data & AI Engineer with deep expertise in the Databricks ecosystem to design, build, and accelerate our next-generation data architecture.

In this role, you won't just write backend pipelines; you will be the bridge between complex data engineering and tangible business value.

A critical measure of success in this role is the ability to rapidly build and execute concrete, high-impact technical demonstrations that showcase the power of unified data and AI.

Because we operate globally, you must thrive in an autonomous, highly flexible environment, collaborating effectively across diverse time zones.

Education: Bachelor's degree , BE/B. Tech in CS or equivalent

Experience: 10+ years

Location : Hyderabad,India

Position : Senior Data & AI Engineer (Databricks Specialist)

Key Responsibilities

Databricks Architecture & Governance

Design and implement robust data pipelines utilizing the Databricks Lakehouse platform. Take ownership of data governance, security, and fine-grained lineage using Unity Catalog.

Rapid Prototyping & Demos

Quickly conceptualize, build, and present functional, end-to-end data and AI demos (e.g., live dashboards, real-time pipelines, or LLM/RAG prototypes) to stakeholders and clients.

Core Data Engineering

Build scalable, efficient ETL/ELT pipelines using Spark (PySpark/SQL), Delta Lake, and structured streaming. Ensure optimal performance tuning, partitioning, and cost-management of Databricks clusters.

Global Collaboration & Autonomy

Work independently with minimal supervision, managing your own schedule to align with global, cross-functional teams.

Required Skills & Qualifications

Databricks & Governance Mastery

Proven track record implementing Databricks Unity Catalog for data governance, access control, and data lineage.

Deep understanding of Databricks architecture, including Delta Lake, serverless compute, and Workflows.

Core Data Engineering Excellence

Strong foundational knowledge of data engineering principles (star schemas, dimensional modeling, data warehousing vs. data lakes).

Advanced proficiency in Python/PySpark and SQL.

Experience building robust orchestrations and handling both batch and real-time streaming data.

Experience in building AI/ML workloads (e.g., MLflow, LLM integration, or RAG frameworks) within Databricks.

Agility & Communication

Exceptional ability to build quick, concrete POCs (Proof of Concepts) and technical demos that clearly translate data capabilities into business solutions.

Excellent communication skills, with the ability to clearly articulate technical concepts to both technical and non-technical audiences.

Preferred Qualifications

Certifications such as Databricks Certified Data Engineer Professionalor Databricks Certified Machine Learning Professional.

Experience integrating Databricks with enterprise ecosystems, cloud provider native services (AWS/Azure/GCP), or modern BI tools.

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